Journal of Manufacturing and Materials Processing Latest open access articles published in J. Manuf. Mater. Process. at https://www.mdpi.com/journal/jmmp https://www.mdpi.com/journal/jmmp MDPI en Creative Commons Attribution (CC-BY) MDPI support@mdpi.com JMMP, Vol. 10, Pages 290: A Critical Review of Assisted Robotic Incremental Sheet Forming of AA5083 Aluminium Alloy: Technical Advances, Industrial Potential and Research Gaps https://www.mdpi.com/2504-4494/10/8/290 The increasing demand for lightweight and corrosion-resistant structures has accelerated the use of AA5083 aluminium alloy in automotive, aerospace, marine and transportation industries owing to its excellent corrosion resistance, weldability and favourable strength-to-weight ratio. However, the fabrication of complex AA5083 components remains challenging because of limited formability, localised thinning, fracture and springback associated with conventional forming processes. Robotic incremental sheet forming (RISF) has emerged as a promising dieless manufacturing technology capable of producing complex and customised components with reduced tooling requirements. Recent developments in assisted RISF, particularly heating-assisted and hydro-assisted approaches, have further enhanced process capability. The reviewed literature consistently demonstrates that heating-assisted RISF improves formability by reducing flow stress and fracture tendency, whereas hydro-assisted RISF provides superior thickness distribution, deformation stability and dimensional accuracy. Despite these advances, significant challenges remain, including the lack of standardised processing conditions, limited comparative studies between cold and assisted RISF, insufficient understanding of hydro-assisted RISF for AA5083, and the absence of comprehensive process–structure–performance correlations. This review critically summarises the principles of ISF, RISF and assisted RISF technologies, evaluates their technical developments, industrial potential and economic considerations, and identifies the major research gaps limiting industrial implementation. Future research should focus on standardised processing methodologies, predictive modelling, integrated process optimisation and comprehensive material characterisation to facilitate the wider adoption of assisted RISF for manufacturing advanced lightweight AA5083 components. 2026-08-08 JMMP, Vol. 10, Pages 290: A Critical Review of Assisted Robotic Incremental Sheet Forming of AA5083 Aluminium Alloy: Technical Advances, Industrial Potential and Research Gaps

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080290

Authors: Yuvraj Narwade Sameer Sayyad Javed Sayyad

The increasing demand for lightweight and corrosion-resistant structures has accelerated the use of AA5083 aluminium alloy in automotive, aerospace, marine and transportation industries owing to its excellent corrosion resistance, weldability and favourable strength-to-weight ratio. However, the fabrication of complex AA5083 components remains challenging because of limited formability, localised thinning, fracture and springback associated with conventional forming processes. Robotic incremental sheet forming (RISF) has emerged as a promising dieless manufacturing technology capable of producing complex and customised components with reduced tooling requirements. Recent developments in assisted RISF, particularly heating-assisted and hydro-assisted approaches, have further enhanced process capability. The reviewed literature consistently demonstrates that heating-assisted RISF improves formability by reducing flow stress and fracture tendency, whereas hydro-assisted RISF provides superior thickness distribution, deformation stability and dimensional accuracy. Despite these advances, significant challenges remain, including the lack of standardised processing conditions, limited comparative studies between cold and assisted RISF, insufficient understanding of hydro-assisted RISF for AA5083, and the absence of comprehensive process–structure–performance correlations. This review critically summarises the principles of ISF, RISF and assisted RISF technologies, evaluates their technical developments, industrial potential and economic considerations, and identifies the major research gaps limiting industrial implementation. Future research should focus on standardised processing methodologies, predictive modelling, integrated process optimisation and comprehensive material characterisation to facilitate the wider adoption of assisted RISF for manufacturing advanced lightweight AA5083 components.

]]> A Critical Review of Assisted Robotic Incremental Sheet Forming of AA5083 Aluminium Alloy: Technical Advances, Industrial Potential and Research Gaps Yuvraj Narwade Sameer Sayyad Javed Sayyad doi: 10.3390/jmmp10080290 Journal of Manufacturing and Materials Processing 2026-08-08 Journal of Manufacturing and Materials Processing 2026-08-08 10 8 Review 290 10.3390/jmmp10080290 https://www.mdpi.com/2504-4494/10/8/290 JMMP, Vol. 10, Pages 289: Glass Additive Manufacturing Technologies: Approaches, Applications, and Challenges https://www.mdpi.com/2504-4494/10/8/289 Glass additive manufacturing (AM) is a developing technology, particularly in comparison to metals and polymers, both of which have had their processes and applications extensively studied. Its potential lies in fabricating complex, even micrometric, geometries that are difficult or impossible to achieve via traditional molding, as well as in producing components with unique optical properties. The diversity of AM techniques, alongside the challenges associated with the high melting point, rheological control, and fragility of glass, necessitates a comprehensive analysis of current developments. Accordingly, this review presents a systematic review, conducted in accordance with the PRISMA protocol, of recent literature regarding AM technologies that fabricate glass via particle fusion to form solid components. This review explicitly excludes techniques utilizing glass fibers as reinforcement, as that constitutes a separate field of inquiry. The results demonstrate sustained growth within the field, with a predominance of technologies based on photopolymerization and ink extrusion, both of which offer high resolution and microstructural control. Ultimately, this review establishes the current state of the art, identifying critical challenges and emerging lines of research to guide future development. It is intended to serve as a foundational reference for researchers and professionals seeking to initiate or expand their work in glass AM. 2026-08-07 JMMP, Vol. 10, Pages 289: Glass Additive Manufacturing Technologies: Approaches, Applications, and Challenges

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080289

Authors: Edwin Francis Cárdenas Correa Edgar Absalón Torres Barahona Alison Dayana García Rodríguez

Glass additive manufacturing (AM) is a developing technology, particularly in comparison to metals and polymers, both of which have had their processes and applications extensively studied. Its potential lies in fabricating complex, even micrometric, geometries that are difficult or impossible to achieve via traditional molding, as well as in producing components with unique optical properties. The diversity of AM techniques, alongside the challenges associated with the high melting point, rheological control, and fragility of glass, necessitates a comprehensive analysis of current developments. Accordingly, this review presents a systematic review, conducted in accordance with the PRISMA protocol, of recent literature regarding AM technologies that fabricate glass via particle fusion to form solid components. This review explicitly excludes techniques utilizing glass fibers as reinforcement, as that constitutes a separate field of inquiry. The results demonstrate sustained growth within the field, with a predominance of technologies based on photopolymerization and ink extrusion, both of which offer high resolution and microstructural control. Ultimately, this review establishes the current state of the art, identifying critical challenges and emerging lines of research to guide future development. It is intended to serve as a foundational reference for researchers and professionals seeking to initiate or expand their work in glass AM.

]]> Glass Additive Manufacturing Technologies: Approaches, Applications, and Challenges Edwin Francis Cárdenas Correa Edgar Absalón Torres Barahona Alison Dayana García Rodríguez doi: 10.3390/jmmp10080289 Journal of Manufacturing and Materials Processing 2026-08-07 Journal of Manufacturing and Materials Processing 2026-08-07 10 8 Review 289 10.3390/jmmp10080289 https://www.mdpi.com/2504-4494/10/8/289 JMMP, Vol. 10, Pages 288: Advanced Surface Protection Strategies for Refurbished Hydropower Components: A Critical Review of Chemical and Manufacturing Approaches https://www.mdpi.com/2504-4494/10/8/288 This paper presents a critical review of surface protection strategies for refurbished hydropower components, with emphasis on the manufacturing and materials-processing logic that links damage mechanisms, substrate condition, deposition route, microstructure, and service performance. The literature indicates that cavitation erosion, sediment abrasion, corrosion, and their synergistic interactions are intensified by flexible and off-design hydropower operation, making refurbishment decisions increasingly surface-sensitive rather than purely bulk-material problems. Thermal spray and laser cladding remain the dominant industrially relevant routes, while cold spray and emerging multi-principal-element, high-entropy, and Fe-based amorphous systems expand the design space for lower heat input, better defect control, and improved cavitation resistance. Across the considered studies, the most consistent conclusion is that hardness alone is not a reliable selection criterion; porosity, interfacial integrity, crack susceptibility, residual stress, and the ability to accommodate local deformation govern real durability. Chemical pre-treatments, sealants, and hybrid finishing routes appear less mature as standalone hydropower solutions, but are important enablers for substrate activation, coating densification, and corrosion mitigation. Therefore, the review proposes a refurbishment-oriented framework in which route selection is based on the initial damage state of the component, the admissible thermal load on the substrate, the required build-up thickness, and the expected cavitation/slurry/corrosion regime. 2026-08-07 JMMP, Vol. 10, Pages 288: Advanced Surface Protection Strategies for Refurbished Hydropower Components: A Critical Review of Chemical and Manufacturing Approaches

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080288

Authors: Gheorghe Daniel Lakatos Gabriella Stefánia Szabó Sára Ferenci Loránd Szabó

This paper presents a critical review of surface protection strategies for refurbished hydropower components, with emphasis on the manufacturing and materials-processing logic that links damage mechanisms, substrate condition, deposition route, microstructure, and service performance. The literature indicates that cavitation erosion, sediment abrasion, corrosion, and their synergistic interactions are intensified by flexible and off-design hydropower operation, making refurbishment decisions increasingly surface-sensitive rather than purely bulk-material problems. Thermal spray and laser cladding remain the dominant industrially relevant routes, while cold spray and emerging multi-principal-element, high-entropy, and Fe-based amorphous systems expand the design space for lower heat input, better defect control, and improved cavitation resistance. Across the considered studies, the most consistent conclusion is that hardness alone is not a reliable selection criterion; porosity, interfacial integrity, crack susceptibility, residual stress, and the ability to accommodate local deformation govern real durability. Chemical pre-treatments, sealants, and hybrid finishing routes appear less mature as standalone hydropower solutions, but are important enablers for substrate activation, coating densification, and corrosion mitigation. Therefore, the review proposes a refurbishment-oriented framework in which route selection is based on the initial damage state of the component, the admissible thermal load on the substrate, the required build-up thickness, and the expected cavitation/slurry/corrosion regime.

]]> Advanced Surface Protection Strategies for Refurbished Hydropower Components: A Critical Review of Chemical and Manufacturing Approaches Gheorghe Daniel Lakatos Gabriella Stefánia Szabó Sára Ferenci Loránd Szabó doi: 10.3390/jmmp10080288 Journal of Manufacturing and Materials Processing 2026-08-07 Journal of Manufacturing and Materials Processing 2026-08-07 10 8 Review 288 10.3390/jmmp10080288 https://www.mdpi.com/2504-4494/10/8/288 JMMP, Vol. 10, Pages 287: Finite Element Simulation of Filling Behaviors in Precision Glass Molding of Fresnel Glass Lenses https://www.mdpi.com/2504-4494/10/8/287 Precision glass molding is a promising yet challenging approach for fabricating Fresnel glass lenses, as their complex multi-ring microstructures tend to induce nonuniform glass flow and incomplete filling. To elucidate the filling behaviors under compression, a thermo-mechanically coupled finite element model was developed to simulate the molding process. The ring filling ratios of each ring and the total lens were adopted as a quantitative metric to systematically investigate the effects of molding temperature, molding pressure, glass–mold interfacial friction coefficient, and the number of Fresnel rings on glass flow and filling behavior. The results show that filling proceeds sequentially from the inner rings to the outer rings. Increasing the interfacial friction coefficient or the number of Fresnel rings significantly increases flow resistance, suppresses radial glass flow, and prolongs the filling time. In contrast, higher molding temperature and pressure promote glass flow, improve the filling efficiency of multi-ring microstructures, and identify the critical processing window for complete filling. These findings provide fundamental insights into the filling behavior of Fresnel microstructures during precision glass molding and offer a theoretical basis for process optimization and the high-precision fabrication of Fresnel lenses. 2026-08-07 JMMP, Vol. 10, Pages 287: Finite Element Simulation of Filling Behaviors in Precision Glass Molding of Fresnel Glass Lenses

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080287

Authors: Renwei Gao Jianmin Tan Jian Zhou

Precision glass molding is a promising yet challenging approach for fabricating Fresnel glass lenses, as their complex multi-ring microstructures tend to induce nonuniform glass flow and incomplete filling. To elucidate the filling behaviors under compression, a thermo-mechanically coupled finite element model was developed to simulate the molding process. The ring filling ratios of each ring and the total lens were adopted as a quantitative metric to systematically investigate the effects of molding temperature, molding pressure, glass–mold interfacial friction coefficient, and the number of Fresnel rings on glass flow and filling behavior. The results show that filling proceeds sequentially from the inner rings to the outer rings. Increasing the interfacial friction coefficient or the number of Fresnel rings significantly increases flow resistance, suppresses radial glass flow, and prolongs the filling time. In contrast, higher molding temperature and pressure promote glass flow, improve the filling efficiency of multi-ring microstructures, and identify the critical processing window for complete filling. These findings provide fundamental insights into the filling behavior of Fresnel microstructures during precision glass molding and offer a theoretical basis for process optimization and the high-precision fabrication of Fresnel lenses.

]]> Finite Element Simulation of Filling Behaviors in Precision Glass Molding of Fresnel Glass Lenses Renwei Gao Jianmin Tan Jian Zhou doi: 10.3390/jmmp10080287 Journal of Manufacturing and Materials Processing 2026-08-07 Journal of Manufacturing and Materials Processing 2026-08-07 10 8 Article 287 10.3390/jmmp10080287 https://www.mdpi.com/2504-4494/10/8/287 JMMP, Vol. 10, Pages 286: MaskLenNet: A Query-Based Instance Segmentation and Length Prediction Network for Quantitative Industrial Tool Wear and Breakage Assessment https://www.mdpi.com/2504-4494/10/8/286 Tool wear detection is essential for machining quality control and predictive maintenance, but conventional inspection is often manual, time-consuming, and operator-dependent. Existing learning-based visual methods still face challenges in jointly achieving reliable wear-type recognition, accurate wear-region localization, and quantitative wear-width measurement under shop-floor imaging conditions. To address these issues, this study proposes MaskLenNet, a query-based instance segmentation and length prediction network for solid carbide end-milling tool diagnosis. MaskLenNet combines a Swin Transformer backbone, query-based instance-mask prediction, wear-oriented attention, and a key-point head that directly estimates the maximum wear-land width (VB). Evaluation uses 234 images from 54 physical tools under a tool-disjoint split, so different rotations of one tool cannot occur in both training and evaluation sets. On the held-out test set, MaskLenNet achieves 96.52% matched-instance classification accuracy, 95.75% foreground instance mIoU, and a VB mean absolute error of 0.010214 mm. Relative to BEiT-Base, the gains are 3.04 and 3.60 percentage points in accuracy and mIoU, respectively. These results demonstrate promising performance within the evaluated acquisition system; they do not establish equivalence to microscopy or generalization to other machines, optics, workpiece materials, or sites. 2026-08-06 JMMP, Vol. 10, Pages 286: MaskLenNet: A Query-Based Instance Segmentation and Length Prediction Network for Quantitative Industrial Tool Wear and Breakage Assessment

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080286

Authors: Yi Pan Kun He Chen Yin Yanping Zhang Yong Luo Yulin Wang

Tool wear detection is essential for machining quality control and predictive maintenance, but conventional inspection is often manual, time-consuming, and operator-dependent. Existing learning-based visual methods still face challenges in jointly achieving reliable wear-type recognition, accurate wear-region localization, and quantitative wear-width measurement under shop-floor imaging conditions. To address these issues, this study proposes MaskLenNet, a query-based instance segmentation and length prediction network for solid carbide end-milling tool diagnosis. MaskLenNet combines a Swin Transformer backbone, query-based instance-mask prediction, wear-oriented attention, and a key-point head that directly estimates the maximum wear-land width (VB). Evaluation uses 234 images from 54 physical tools under a tool-disjoint split, so different rotations of one tool cannot occur in both training and evaluation sets. On the held-out test set, MaskLenNet achieves 96.52% matched-instance classification accuracy, 95.75% foreground instance mIoU, and a VB mean absolute error of 0.010214 mm. Relative to BEiT-Base, the gains are 3.04 and 3.60 percentage points in accuracy and mIoU, respectively. These results demonstrate promising performance within the evaluated acquisition system; they do not establish equivalence to microscopy or generalization to other machines, optics, workpiece materials, or sites.

]]> MaskLenNet: A Query-Based Instance Segmentation and Length Prediction Network for Quantitative Industrial Tool Wear and Breakage Assessment Yi Pan Kun He Chen Yin Yanping Zhang Yong Luo Yulin Wang doi: 10.3390/jmmp10080286 Journal of Manufacturing and Materials Processing 2026-08-06 Journal of Manufacturing and Materials Processing 2026-08-06 10 8 Article 286 10.3390/jmmp10080286 https://www.mdpi.com/2504-4494/10/8/286 JMMP, Vol. 10, Pages 285: Adaptive Hydrodynamic Cavitation in a Reconfigurable Circular Venturi: Design Framework and Numerical Demonstration of a Parametric Cavitation-Inception Workflow https://www.mdpi.com/2504-4494/10/8/285 Hydrodynamic cavitation is increasingly investigated as a process-intensification technology for liquid processing and complex or waste-derived streams. Conventional Venturi cavitators rely on fixed geometries selected for nominal operating conditions, whereas practical processes may involve variable fluid properties, flow rates, pressure conditions, and treatment objectives. This mismatch can produce unstable cavitation regimes, excessive or insufficient treatment severity, and inefficient use of pressure energy. This article introduces the Dynamic Circular Venturi Adaptive (DCVA), a reconfigurable circular Venturi framework in which the internal profile is treated as an operating variable rather than only as a fixed design feature. Unlike the previously proposed Dynamic Venturi Reuleaux Actuated (DVRA) concept, which uses a non-circular Reuleaux-section Venturi with boundary-imposed swirl, the DCVA retains an axisymmetric circular geometry and relies on controlled profile reconfiguration without swirl forcing. The framework defines equivalent geometric parameters, an admissible design space, plant-measurable operating indicators, and representative architectures for single-parameter and multiparametric reconfiguration. A numerical demonstration of the parametric design workflow is provided using an automated axisymmetric finite-element computational fluid dynamics (CFD) procedure that links CAD generation, meshing, flow simulation, post-processing, and iterative geometry updating to identify the throat configuration associated with cavitation inception. The results support CFD-assisted configuration selection, commissioning-map development, and future supervisory control, while prototype realization and experimental benchmarking remain necessary for full device-level validation. 2026-08-06 JMMP, Vol. 10, Pages 285: Adaptive Hydrodynamic Cavitation in a Reconfigurable Circular Venturi: Design Framework and Numerical Demonstration of a Parametric Cavitation-Inception Workflow

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080285

Authors: Lorenzo Albanese Federico Rotini

Hydrodynamic cavitation is increasingly investigated as a process-intensification technology for liquid processing and complex or waste-derived streams. Conventional Venturi cavitators rely on fixed geometries selected for nominal operating conditions, whereas practical processes may involve variable fluid properties, flow rates, pressure conditions, and treatment objectives. This mismatch can produce unstable cavitation regimes, excessive or insufficient treatment severity, and inefficient use of pressure energy. This article introduces the Dynamic Circular Venturi Adaptive (DCVA), a reconfigurable circular Venturi framework in which the internal profile is treated as an operating variable rather than only as a fixed design feature. Unlike the previously proposed Dynamic Venturi Reuleaux Actuated (DVRA) concept, which uses a non-circular Reuleaux-section Venturi with boundary-imposed swirl, the DCVA retains an axisymmetric circular geometry and relies on controlled profile reconfiguration without swirl forcing. The framework defines equivalent geometric parameters, an admissible design space, plant-measurable operating indicators, and representative architectures for single-parameter and multiparametric reconfiguration. A numerical demonstration of the parametric design workflow is provided using an automated axisymmetric finite-element computational fluid dynamics (CFD) procedure that links CAD generation, meshing, flow simulation, post-processing, and iterative geometry updating to identify the throat configuration associated with cavitation inception. The results support CFD-assisted configuration selection, commissioning-map development, and future supervisory control, while prototype realization and experimental benchmarking remain necessary for full device-level validation.

]]> Adaptive Hydrodynamic Cavitation in a Reconfigurable Circular Venturi: Design Framework and Numerical Demonstration of a Parametric Cavitation-Inception Workflow Lorenzo Albanese Federico Rotini doi: 10.3390/jmmp10080285 Journal of Manufacturing and Materials Processing 2026-08-06 Journal of Manufacturing and Materials Processing 2026-08-06 10 8 Article 285 10.3390/jmmp10080285 https://www.mdpi.com/2504-4494/10/8/285 JMMP, Vol. 10, Pages 284: Surface Reaction Layer Evolution and Material Removal Mechanism in Chemical-Assisted Magnetorheological Finishing of 316L Stainless Steel Capillaries https://www.mdpi.com/2504-4494/10/8/284 316L stainless-steel capillary tubes are important in medical devices, precision fluid transport and micro heat exchangers, but their slender geometry and dense passivation film make inner-surface finishing inefficient. This study proposes a stepwise chemical-assisted magnetorheological finishing (CMRF) process for 316L capillaries. The inner surface was first pretreated with hydrogen peroxide/oxalic acid to form a removable reaction layer, and then finished by magnetorheological abrasives. The effects of the two reagents on material removal and surface integrity were evaluated, and the optimal pretreatment was determined to be 2.25 wt.% oxalic acid and 1.5 wt.% H2O2. Compared with conventional magnetorheological finishing, CMRF increased the material removal rate by approximately 54% and reduced the final inner-surface roughness Sa to 0.116 μm. Characterization results show that hydrogen peroxide and oxalic acid generate a dynamic oxidation–complexation–dissolution–reoxidation cycle, converting the dense passive film into an oxygen-rich, porous, low-crystallinity reaction layer and reducing surface hardness by about 30%. This softened layer promotes preferential abrasive removal instead of direct cutting of the metallic substrate, thereby improving finishing efficiency and surface quality. 2026-08-06 JMMP, Vol. 10, Pages 284: Surface Reaction Layer Evolution and Material Removal Mechanism in Chemical-Assisted Magnetorheological Finishing of 316L Stainless Steel Capillaries

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080284

Authors: Yefeng Yang Zhaoyang Luo Pavel Lushchyk Bing Guo Chunya Wu

316L stainless-steel capillary tubes are important in medical devices, precision fluid transport and micro heat exchangers, but their slender geometry and dense passivation film make inner-surface finishing inefficient. This study proposes a stepwise chemical-assisted magnetorheological finishing (CMRF) process for 316L capillaries. The inner surface was first pretreated with hydrogen peroxide/oxalic acid to form a removable reaction layer, and then finished by magnetorheological abrasives. The effects of the two reagents on material removal and surface integrity were evaluated, and the optimal pretreatment was determined to be 2.25 wt.% oxalic acid and 1.5 wt.% H2O2. Compared with conventional magnetorheological finishing, CMRF increased the material removal rate by approximately 54% and reduced the final inner-surface roughness Sa to 0.116 μm. Characterization results show that hydrogen peroxide and oxalic acid generate a dynamic oxidation–complexation–dissolution–reoxidation cycle, converting the dense passive film into an oxygen-rich, porous, low-crystallinity reaction layer and reducing surface hardness by about 30%. This softened layer promotes preferential abrasive removal instead of direct cutting of the metallic substrate, thereby improving finishing efficiency and surface quality.

]]> Surface Reaction Layer Evolution and Material Removal Mechanism in Chemical-Assisted Magnetorheological Finishing of 316L Stainless Steel Capillaries Yefeng Yang Zhaoyang Luo Pavel Lushchyk Bing Guo Chunya Wu doi: 10.3390/jmmp10080284 Journal of Manufacturing and Materials Processing 2026-08-06 Journal of Manufacturing and Materials Processing 2026-08-06 10 8 Article 284 10.3390/jmmp10080284 https://www.mdpi.com/2504-4494/10/8/284 JMMP, Vol. 10, Pages 283: Influence of Laser Spot Size on the Microstructure, Transformation Temperatures, and Ni Content of a Nickel-Rich LPBF Ti-Ni Alloy https://www.mdpi.com/2504-4494/10/8/283 This study investigates the influence of laser spot size (Ø100 µm vs. Ø50 µm) on the microstructure, transformation behavior, and hardness of Ti-51.17 at.%Ni shape memory alloy samples fabricated by laser powder bed fusion. Samples were produced using identical processing parameters covering laser powers of 50–150 W, scanning speeds of 500–750 mm/s, and matched volumetric energy densities (28–83 J/mm3), with spot size as the only variable. Although both laser spot sizes produced comparable melt pool geometries and predominantly B2 austenite matrices with minor fractions of B19′ martensite, the Ø50 µm samples exhibited finer microstructures, higher residual stresses, and lower martensitic transformation temperatures in the as-built state. Heat treatment at 800 °C reduced residual stresses and partially homogenized the microstructure; however, differences in their transformation behavior remained. These differences were attributed to the spot-size-dependent Ni evaporation. Although transformation temperatures increased with increasing energy density for both conditions, the Ø50 µm samples consistently showed lower values. In the 55–83 J/mm3 volumetric energy density range, the estimated Ni content ranged from 51.15 to 50.42 at.%, and the Ø50 µm samples showed approximately 0.1–0.2 at.% greater Ni loss than their Ø100 µm counterparts. These findings demonstrate that Ni evaporation is a laser-spot-size-dependent phenomenon that must be considered when processing near-equiatomic Ti-Ni alloys. 2026-08-06 JMMP, Vol. 10, Pages 283: Influence of Laser Spot Size on the Microstructure, Transformation Temperatures, and Ni Content of a Nickel-Rich LPBF Ti-Ni Alloy

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080283

Authors: Alena Kreitcberg Donatien Campion Emma Bisserié Vladimir Brailovski

This study investigates the influence of laser spot size (Ø100 µm vs. Ø50 µm) on the microstructure, transformation behavior, and hardness of Ti-51.17 at.%Ni shape memory alloy samples fabricated by laser powder bed fusion. Samples were produced using identical processing parameters covering laser powers of 50–150 W, scanning speeds of 500–750 mm/s, and matched volumetric energy densities (28–83 J/mm3), with spot size as the only variable. Although both laser spot sizes produced comparable melt pool geometries and predominantly B2 austenite matrices with minor fractions of B19′ martensite, the Ø50 µm samples exhibited finer microstructures, higher residual stresses, and lower martensitic transformation temperatures in the as-built state. Heat treatment at 800 °C reduced residual stresses and partially homogenized the microstructure; however, differences in their transformation behavior remained. These differences were attributed to the spot-size-dependent Ni evaporation. Although transformation temperatures increased with increasing energy density for both conditions, the Ø50 µm samples consistently showed lower values. In the 55–83 J/mm3 volumetric energy density range, the estimated Ni content ranged from 51.15 to 50.42 at.%, and the Ø50 µm samples showed approximately 0.1–0.2 at.% greater Ni loss than their Ø100 µm counterparts. These findings demonstrate that Ni evaporation is a laser-spot-size-dependent phenomenon that must be considered when processing near-equiatomic Ti-Ni alloys.

]]> Influence of Laser Spot Size on the Microstructure, Transformation Temperatures, and Ni Content of a Nickel-Rich LPBF Ti-Ni Alloy Alena Kreitcberg Donatien Campion Emma Bisserié Vladimir Brailovski doi: 10.3390/jmmp10080283 Journal of Manufacturing and Materials Processing 2026-08-06 Journal of Manufacturing and Materials Processing 2026-08-06 10 8 Article 283 10.3390/jmmp10080283 https://www.mdpi.com/2504-4494/10/8/283 JMMP, Vol. 10, Pages 282: Substrate-Assisted Binder Jetting of M2 High-Speed Steel: Mechanisms of Printing Defects and Sintering Densification Behavior https://www.mdpi.com/2504-4494/10/8/282 Binder jetting (BJ) can avoid crack defects caused by residual thermal stress in the additive manufacturing of high-speed steel (HSS). However, the research on BJ-fabricated HSS remains limited and the printing and sintering processes for M2 HSS are still not well understood. The mechanisms of printing defects and microstructure evolution behavior have not been fully elucidated. In this research, orthogonal experiments are designed and conducted to investigate the effects of layer thickness, inkjet concentration, and powder spreading speed on the forming quality (relative density) of green parts. The types and causes of printing defects are identified and the formation mechanism of layer-shifting defects is analyzed. A method involving an additional printing base is proposed to eliminate layer shifting. An optimized debinding-sintering curve is established and the influence of sintering temperatures (1280–1320 °C) on the relative density, dimensional shrinkage, pore morphology, microstructure, and mechanical properties of BJ M2 HSS is investigated. The transformation mechanisms of carbides are elucidated. The study shows that the BJ M2 HSS achieves a relative density of 99.06% and an average friction coefficient of 0.37 at 1320 °C, with ultimate tensile strength and hardness reaching 858.7 MPa and 628.4 HV. Furthermore, the effects of substrates with different thermal conductivities (graphite and zirconia) on the relative density and warpage of sintered M2 HSS parts are analyzed. The substrates with high thermal conductivity can enhance sintering efficiency but exacerbate deformation. To address this, a graphite-zirconia composite substrate is developed. The results of this study can provide a theoretical foundation for the binder jetting fabrication of high-performance, defect-free M2 HSS. 2026-08-05 JMMP, Vol. 10, Pages 282: Substrate-Assisted Binder Jetting of M2 High-Speed Steel: Mechanisms of Printing Defects and Sintering Densification Behavior

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080282

Authors: Zilin Huang Zhanqiang Liu Jinfu Zhao Bing Wang

Binder jetting (BJ) can avoid crack defects caused by residual thermal stress in the additive manufacturing of high-speed steel (HSS). However, the research on BJ-fabricated HSS remains limited and the printing and sintering processes for M2 HSS are still not well understood. The mechanisms of printing defects and microstructure evolution behavior have not been fully elucidated. In this research, orthogonal experiments are designed and conducted to investigate the effects of layer thickness, inkjet concentration, and powder spreading speed on the forming quality (relative density) of green parts. The types and causes of printing defects are identified and the formation mechanism of layer-shifting defects is analyzed. A method involving an additional printing base is proposed to eliminate layer shifting. An optimized debinding-sintering curve is established and the influence of sintering temperatures (1280–1320 °C) on the relative density, dimensional shrinkage, pore morphology, microstructure, and mechanical properties of BJ M2 HSS is investigated. The transformation mechanisms of carbides are elucidated. The study shows that the BJ M2 HSS achieves a relative density of 99.06% and an average friction coefficient of 0.37 at 1320 °C, with ultimate tensile strength and hardness reaching 858.7 MPa and 628.4 HV. Furthermore, the effects of substrates with different thermal conductivities (graphite and zirconia) on the relative density and warpage of sintered M2 HSS parts are analyzed. The substrates with high thermal conductivity can enhance sintering efficiency but exacerbate deformation. To address this, a graphite-zirconia composite substrate is developed. The results of this study can provide a theoretical foundation for the binder jetting fabrication of high-performance, defect-free M2 HSS.

]]> Substrate-Assisted Binder Jetting of M2 High-Speed Steel: Mechanisms of Printing Defects and Sintering Densification Behavior Zilin Huang Zhanqiang Liu Jinfu Zhao Bing Wang doi: 10.3390/jmmp10080282 Journal of Manufacturing and Materials Processing 2026-08-05 Journal of Manufacturing and Materials Processing 2026-08-05 10 8 Article 282 10.3390/jmmp10080282 https://www.mdpi.com/2504-4494/10/8/282 JMMP, Vol. 10, Pages 281: Research on the Temperature Control and Protection Effects of Low-Temperature Nitrogen on the Water Jet Cutting Process of Alloy Steel https://www.mdpi.com/2504-4494/10/8/281 During abrasive waterjet cutting of alloy steel in complex field environments, local heat sources can induce temperature rise and oxidation risk. To address this issue, this study proposes a low-temperature nitrogen jet (LTNJ) method for simultaneous local cooling and air displacement near the cutting zone. A three-dimensional fluid-solid coupled heat-transfer and species-transport numerical model was established to investigate the coupled cooling and gas-coverage behavior. The study was further supported by infrared thermal-imaging measurements, in which the measured maximum apparent surface temperature remained within 32.1–33.6 °C during cutting under LTNJ assistance. The simulation results show that a nitrogen-enriched low-oxygen coverage region can be formed above the local heat source; for example, when the local nitrogen volume fraction reaches 64.74%, the estimated oxygen volume fraction decreases to approximately 7.39%. The gas temperature above the heat source decreases by more than 240 °C under the simulated conditions, and the relative position between the nozzle and heat source is the dominant factor affecting local cooling and gas coverage. Considering cooling effect, nitrogen utilization, and field implementation feasibility, the recommended parameter combination within the simulated range is a 10 mm horizontal distance between nozzle axis and heat-source center, a 30 mm vertical distance from nozzle outlet to workpiece surface, an initial nitrogen temperature of −50 °C, and a nitrogen flow rate of 5 m3/h. These results provide a numerical and preliminary experimental basis for low-temperature nitrogen-assisted temperature control and low-oxygen protection during abrasive waterjet cutting in complex field environments. 2026-08-05 JMMP, Vol. 10, Pages 281: Research on the Temperature Control and Protection Effects of Low-Temperature Nitrogen on the Water Jet Cutting Process of Alloy Steel

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080281

Authors: Fenglong Yin Yanxia Li Xinyi Zhang Ye Sun Zehan Li

During abrasive waterjet cutting of alloy steel in complex field environments, local heat sources can induce temperature rise and oxidation risk. To address this issue, this study proposes a low-temperature nitrogen jet (LTNJ) method for simultaneous local cooling and air displacement near the cutting zone. A three-dimensional fluid-solid coupled heat-transfer and species-transport numerical model was established to investigate the coupled cooling and gas-coverage behavior. The study was further supported by infrared thermal-imaging measurements, in which the measured maximum apparent surface temperature remained within 32.1–33.6 °C during cutting under LTNJ assistance. The simulation results show that a nitrogen-enriched low-oxygen coverage region can be formed above the local heat source; for example, when the local nitrogen volume fraction reaches 64.74%, the estimated oxygen volume fraction decreases to approximately 7.39%. The gas temperature above the heat source decreases by more than 240 °C under the simulated conditions, and the relative position between the nozzle and heat source is the dominant factor affecting local cooling and gas coverage. Considering cooling effect, nitrogen utilization, and field implementation feasibility, the recommended parameter combination within the simulated range is a 10 mm horizontal distance between nozzle axis and heat-source center, a 30 mm vertical distance from nozzle outlet to workpiece surface, an initial nitrogen temperature of −50 °C, and a nitrogen flow rate of 5 m3/h. These results provide a numerical and preliminary experimental basis for low-temperature nitrogen-assisted temperature control and low-oxygen protection during abrasive waterjet cutting in complex field environments.

]]> Research on the Temperature Control and Protection Effects of Low-Temperature Nitrogen on the Water Jet Cutting Process of Alloy Steel Fenglong Yin Yanxia Li Xinyi Zhang Ye Sun Zehan Li doi: 10.3390/jmmp10080281 Journal of Manufacturing and Materials Processing 2026-08-05 Journal of Manufacturing and Materials Processing 2026-08-05 10 8 Article 281 10.3390/jmmp10080281 https://www.mdpi.com/2504-4494/10/8/281 JMMP, Vol. 10, Pages 280: Sustainable Aerospace Brackets from Recycled Carbon Fiber/PEI Tapes: Life Cycle, Microstructure, and Structural Validation https://www.mdpi.com/2504-4494/10/8/280 Aligned recycled carbon fiber (rCF)/polyetherimide (PEI) tapes are a promising material for lightweight aerospace thermoplastic composite structures with reduced environmental impact, provided that their directional properties can be translated into robust components. To assess the viability of rCF/PEI for aircraft interior applications, this study tracks the development of the “Eco Bracket” across four key stages: sustainability screening, coupon characterization, microstructural interpretation, and application-level structural assessment. A project-level life-cycle assessment compared an Additive Fusion Technology (AFT) rCF/PEI bracket with cast and milled aluminum routes and yielded a short-term climate impact of 0.678 kg CO2-eq for rCF/PEI, representing a significant reduction compared to 5.1 kg CO2-eq for cast aluminum and 20.9 kg CO2-eq for milled aluminum. Coupon testing characterized the anisotropic mechanical response of the rCF/PEI tape, including the elastic moduli and strengths under axial and transverse tension, in-plane shear, and axial and transverse compression. Scanning electron microscopy of a representative fracture surface showed a rough, fiber-dominated morphology with exposed fiber bundles, pull-out, and local variations in matrix coverage, supporting the interpretation that consolidation and local wet-out quality govern the transfer from coupon capability to component performance. At the application level, the manufactured rCF/PEI bracket achieved a peak load of 3517.6 N, corresponding to 93% of the strength of an industry-standard polyetherketoneketone (PEKK) reference bracket, and failed in the fastener-hole region predicted as critical by the finite element model. The combined results indicate that aligned rCF/PEI tapes can deliver mechanical properties consistent with the design requirements of aircraft interior brackets, while process robustness, fiber-path fidelity, and local consolidation quality remain the key barriers to repeatable component performance. 2026-08-05 JMMP, Vol. 10, Pages 280: Sustainable Aerospace Brackets from Recycled Carbon Fiber/PEI Tapes: Life Cycle, Microstructure, and Structural Validation

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080280

Authors: Christian Brauner Florian Givel Julian Kupski Mohammad Hajikazemi

Aligned recycled carbon fiber (rCF)/polyetherimide (PEI) tapes are a promising material for lightweight aerospace thermoplastic composite structures with reduced environmental impact, provided that their directional properties can be translated into robust components. To assess the viability of rCF/PEI for aircraft interior applications, this study tracks the development of the “Eco Bracket” across four key stages: sustainability screening, coupon characterization, microstructural interpretation, and application-level structural assessment. A project-level life-cycle assessment compared an Additive Fusion Technology (AFT) rCF/PEI bracket with cast and milled aluminum routes and yielded a short-term climate impact of 0.678 kg CO2-eq for rCF/PEI, representing a significant reduction compared to 5.1 kg CO2-eq for cast aluminum and 20.9 kg CO2-eq for milled aluminum. Coupon testing characterized the anisotropic mechanical response of the rCF/PEI tape, including the elastic moduli and strengths under axial and transverse tension, in-plane shear, and axial and transverse compression. Scanning electron microscopy of a representative fracture surface showed a rough, fiber-dominated morphology with exposed fiber bundles, pull-out, and local variations in matrix coverage, supporting the interpretation that consolidation and local wet-out quality govern the transfer from coupon capability to component performance. At the application level, the manufactured rCF/PEI bracket achieved a peak load of 3517.6 N, corresponding to 93% of the strength of an industry-standard polyetherketoneketone (PEKK) reference bracket, and failed in the fastener-hole region predicted as critical by the finite element model. The combined results indicate that aligned rCF/PEI tapes can deliver mechanical properties consistent with the design requirements of aircraft interior brackets, while process robustness, fiber-path fidelity, and local consolidation quality remain the key barriers to repeatable component performance.

]]> Sustainable Aerospace Brackets from Recycled Carbon Fiber/PEI Tapes: Life Cycle, Microstructure, and Structural Validation Christian Brauner Florian Givel Julian Kupski Mohammad Hajikazemi doi: 10.3390/jmmp10080280 Journal of Manufacturing and Materials Processing 2026-08-05 Journal of Manufacturing and Materials Processing 2026-08-05 10 8 Article 280 10.3390/jmmp10080280 https://www.mdpi.com/2504-4494/10/8/280 JMMP, Vol. 10, Pages 279: Effects of Recycled ABS Content on Extrusion Stability, Diameter Variability, and Mechanical Response of Filaments for FFF/FDM Printing https://www.mdpi.com/2504-4494/10/8/279 This study addresses the production of 3D printing filament by extrusion from acrylonitrile butadiene styrene blends containing virgin and recycled material. The effect of recycled acrylonitrile butadiene styrene content on selected quality indicators was investigated, with particular emphasis on mechanical response and filament diameter stability. Dimensional stability was considered a critical quality parameter, as diameter fluctuations directly affect material flow consistency during subsequent FFF/FDM processing and may contribute to extrusion-related defects. The fracture surface morphology of the tested filaments was evaluated by optical microscopy. Based on experimental measurements and data analysis, recommendations are proposed to improve the stability of the filament extrusion process when processing ABS blends containing recycled material. 2026-08-03 JMMP, Vol. 10, Pages 279: Effects of Recycled ABS Content on Extrusion Stability, Diameter Variability, and Mechanical Response of Filaments for FFF/FDM Printing

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080279

Authors: Zuzana Mitaľová Jakub Kaščak Marek Kočiško Daniel Dorko

This study addresses the production of 3D printing filament by extrusion from acrylonitrile butadiene styrene blends containing virgin and recycled material. The effect of recycled acrylonitrile butadiene styrene content on selected quality indicators was investigated, with particular emphasis on mechanical response and filament diameter stability. Dimensional stability was considered a critical quality parameter, as diameter fluctuations directly affect material flow consistency during subsequent FFF/FDM processing and may contribute to extrusion-related defects. The fracture surface morphology of the tested filaments was evaluated by optical microscopy. Based on experimental measurements and data analysis, recommendations are proposed to improve the stability of the filament extrusion process when processing ABS blends containing recycled material.

]]> Effects of Recycled ABS Content on Extrusion Stability, Diameter Variability, and Mechanical Response of Filaments for FFF/FDM Printing Zuzana Mitaľová Jakub Kaščak Marek Kočiško Daniel Dorko doi: 10.3390/jmmp10080279 Journal of Manufacturing and Materials Processing 2026-08-03 Journal of Manufacturing and Materials Processing 2026-08-03 10 8 Article 279 10.3390/jmmp10080279 https://www.mdpi.com/2504-4494/10/8/279 JMMP, Vol. 10, Pages 278: Dynamic and Post-Deformation Static Aging as an Integrated Approach to Thermomechanical Processing of TiNi Shape Memory Alloys https://www.mdpi.com/2504-4494/10/8/278 The effect of thermomechanical processing (TMP) parameters on the structural-phase evolution and properties of Ni-enriched Ti–50.8 at.% Ni shape memory alloy was investigated. Compression deformation was performed at T = 300–500 °C, accompanied by the development of dynamic aging (DA) processes, to true strains of e = 0.5–1.3, followed by post-deformation static aging (SA) at 430 °C for 1 and 10 h. The structural-phase state and properties were characterized using optical and transmission electron microscopy, X-ray diffraction, differential scanning calorimetry, and Vickers hardness measurements. The results confirmed that DA processes were activated during compression but proved insufficient for pronounced Ti3Ni4 precipitate growth compared with SA. The temperature range of 430–500 °C promoted the most intensive DA processes and facilitated ultrafine-grained structure formation. The processing route combining DA at 500 °C with short-term SA (1 h) resulted in the finest precipitates of Ti3Ni4 phase and most homogeneous substructure. These findings demonstrate that the proposed TMP strategy enables effective tailoring of precipitate dispersion, evolution of transformation temperatures and mechanical properties (hardness), providing a viable manufacturing pathway for tailoring TiNi SMA performance in advanced biomedical and engineering applications. 2026-08-03 JMMP, Vol. 10, Pages 278: Dynamic and Post-Deformation Static Aging as an Integrated Approach to Thermomechanical Processing of TiNi Shape Memory Alloys

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080278

Authors: Victor Komarov Vladimir Cherkasov Roman Karelin Weisi Cai Irina Khmelevskaya Vladimir Andreev Ulrich Prahl Vladimir Yusupov Chao Yang Sergey Prokoshkin

The effect of thermomechanical processing (TMP) parameters on the structural-phase evolution and properties of Ni-enriched Ti–50.8 at.% Ni shape memory alloy was investigated. Compression deformation was performed at T = 300–500 °C, accompanied by the development of dynamic aging (DA) processes, to true strains of e = 0.5–1.3, followed by post-deformation static aging (SA) at 430 °C for 1 and 10 h. The structural-phase state and properties were characterized using optical and transmission electron microscopy, X-ray diffraction, differential scanning calorimetry, and Vickers hardness measurements. The results confirmed that DA processes were activated during compression but proved insufficient for pronounced Ti3Ni4 precipitate growth compared with SA. The temperature range of 430–500 °C promoted the most intensive DA processes and facilitated ultrafine-grained structure formation. The processing route combining DA at 500 °C with short-term SA (1 h) resulted in the finest precipitates of Ti3Ni4 phase and most homogeneous substructure. These findings demonstrate that the proposed TMP strategy enables effective tailoring of precipitate dispersion, evolution of transformation temperatures and mechanical properties (hardness), providing a viable manufacturing pathway for tailoring TiNi SMA performance in advanced biomedical and engineering applications.

]]> Dynamic and Post-Deformation Static Aging as an Integrated Approach to Thermomechanical Processing of TiNi Shape Memory Alloys Victor Komarov Vladimir Cherkasov Roman Karelin Weisi Cai Irina Khmelevskaya Vladimir Andreev Ulrich Prahl Vladimir Yusupov Chao Yang Sergey Prokoshkin doi: 10.3390/jmmp10080278 Journal of Manufacturing and Materials Processing 2026-08-03 Journal of Manufacturing and Materials Processing 2026-08-03 10 8 Article 278 10.3390/jmmp10080278 https://www.mdpi.com/2504-4494/10/8/278 JMMP, Vol. 10, Pages 277: Investigation on Wear Evolution Behavior of Pyramid Belt in Grinding of GH4169 Superalloy https://www.mdpi.com/2504-4494/10/8/277 Owing to its unique pyramid-shaped stacked abrasive structure, the pyramid belt pro-vides fine and uniform grinding performance, making it increasingly attractive for precision grinding applications. However, the wear evolution behavior of such belts during the grinding of GH4169 superalloy has not yet been systematically understood. In this study, a full-life-cycle pyramid belt wear experiment in grinding of GH4169 was conducted under fixed conditions. Three monitoring points were arranged along the belt length, and the same abrasive agglomerate arrays were repeatedly tracked using a digital microscope and optical profilometer, while a scanning electron microscope was used to identify the wear mechanisms. The results show that the main wear modes include agglomerate flat wear, fracture, pull-out, and metal adhesion, with flat wear dominating throughout most of the belt life. Across the belt width, the wear height exhibits an approximately symmetric distribution, with more severe wear in the central region. Temporally, the wear process comprises an initial rapid-wear stage followed by a steady-wear stage. In addition, belt wear evolution significantly affects the ground surface roughness, which first decreases and then increases with wear progression. These findings clarify the material-specific wear characteristics of the pyramid belt during GH4169 grinding and reveal the spatial and temporal characteristics of its wear evolution. 2026-08-03 JMMP, Vol. 10, Pages 277: Investigation on Wear Evolution Behavior of Pyramid Belt in Grinding of GH4169 Superalloy

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080277

Authors: Zhijian Tao Rui Xu Songjiaming Liu Xin Huang Zhao Zhang Junde Qi Dinghua Zhang

Owing to its unique pyramid-shaped stacked abrasive structure, the pyramid belt pro-vides fine and uniform grinding performance, making it increasingly attractive for precision grinding applications. However, the wear evolution behavior of such belts during the grinding of GH4169 superalloy has not yet been systematically understood. In this study, a full-life-cycle pyramid belt wear experiment in grinding of GH4169 was conducted under fixed conditions. Three monitoring points were arranged along the belt length, and the same abrasive agglomerate arrays were repeatedly tracked using a digital microscope and optical profilometer, while a scanning electron microscope was used to identify the wear mechanisms. The results show that the main wear modes include agglomerate flat wear, fracture, pull-out, and metal adhesion, with flat wear dominating throughout most of the belt life. Across the belt width, the wear height exhibits an approximately symmetric distribution, with more severe wear in the central region. Temporally, the wear process comprises an initial rapid-wear stage followed by a steady-wear stage. In addition, belt wear evolution significantly affects the ground surface roughness, which first decreases and then increases with wear progression. These findings clarify the material-specific wear characteristics of the pyramid belt during GH4169 grinding and reveal the spatial and temporal characteristics of its wear evolution.

]]> Investigation on Wear Evolution Behavior of Pyramid Belt in Grinding of GH4169 Superalloy Zhijian Tao Rui Xu Songjiaming Liu Xin Huang Zhao Zhang Junde Qi Dinghua Zhang doi: 10.3390/jmmp10080277 Journal of Manufacturing and Materials Processing 2026-08-03 Journal of Manufacturing and Materials Processing 2026-08-03 10 8 Article 277 10.3390/jmmp10080277 https://www.mdpi.com/2504-4494/10/8/277 JMMP, Vol. 10, Pages 276: Optimization of High-Volume PCB Assembly: A Lean Six Sigma Approach Through Pin-in-Paste Technology Integration https://www.mdpi.com/2504-4494/10/8/276 The dual reliance on surface-mount technology (SMT) and pin-through-hole (PTH) assembly lines in high-volume printed circuit board (PCB) manufacturing induces logistical bottlenecks, excessive operational costs, and elevated thermal stress on components. This study presents the optimization of a wireless detector terminal production line by integrating Pin-in-Paste (PiP) technology within a Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) framework. By accurately calculating the required solder volume (Vreq) and stencil aperture dimensions based on pin and pad geometries, the wave soldering process was eliminated without altering existing thermal profiles. The integration consolidated the assembly into a single heat cycle, ensuring IPC-A-610 Class 2 compliance for barrel fill ratios. The results demonstrate a 97% reduction in average assembly costs, yielding annual savings of USD 92,513 while eliminating USD 44,025 in work-in-progress (WIP) inventory. Furthermore, the single-reflow approach mitigated component thermal degradation and reduced the facility’s carbon footprint by an estimated 13.32–17.76 metric tons of CO2 equivalent annually. This research validates a comprehensive methodology for transitioning to PiP technology, offering a sustainable, cost-effective framework for operational excellence in the electronics’ manufacturing industry. 2026-08-02 JMMP, Vol. 10, Pages 276: Optimization of High-Volume PCB Assembly: A Lean Six Sigma Approach Through Pin-in-Paste Technology Integration

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080276

Authors: Cosme Juan-Velázquez Alfredo Villanueva-Montellano José Omar Dávalos-Ramírez Betania Sánchez-Santamaria Manuel Alejandro Lira-Martínez Guillermo Mejía-Cisneros Delfino Cornejo-Monroy

The dual reliance on surface-mount technology (SMT) and pin-through-hole (PTH) assembly lines in high-volume printed circuit board (PCB) manufacturing induces logistical bottlenecks, excessive operational costs, and elevated thermal stress on components. This study presents the optimization of a wireless detector terminal production line by integrating Pin-in-Paste (PiP) technology within a Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) framework. By accurately calculating the required solder volume (Vreq) and stencil aperture dimensions based on pin and pad geometries, the wave soldering process was eliminated without altering existing thermal profiles. The integration consolidated the assembly into a single heat cycle, ensuring IPC-A-610 Class 2 compliance for barrel fill ratios. The results demonstrate a 97% reduction in average assembly costs, yielding annual savings of USD 92,513 while eliminating USD 44,025 in work-in-progress (WIP) inventory. Furthermore, the single-reflow approach mitigated component thermal degradation and reduced the facility’s carbon footprint by an estimated 13.32–17.76 metric tons of CO2 equivalent annually. This research validates a comprehensive methodology for transitioning to PiP technology, offering a sustainable, cost-effective framework for operational excellence in the electronics’ manufacturing industry.

]]> Optimization of High-Volume PCB Assembly: A Lean Six Sigma Approach Through Pin-in-Paste Technology Integration Cosme Juan-Velázquez Alfredo Villanueva-Montellano José Omar Dávalos-Ramírez Betania Sánchez-Santamaria Manuel Alejandro Lira-Martínez Guillermo Mejía-Cisneros Delfino Cornejo-Monroy doi: 10.3390/jmmp10080276 Journal of Manufacturing and Materials Processing 2026-08-02 Journal of Manufacturing and Materials Processing 2026-08-02 10 8 Article 276 10.3390/jmmp10080276 https://www.mdpi.com/2504-4494/10/8/276 JMMP, Vol. 10, Pages 275: Data-Driven Modeling of Thermal Regulation in CFRP Drilling: RSM-Based Combined Effects of Wax and Graphene Additives https://www.mdpi.com/2504-4494/10/8/275 Carbon fiber-reinforced polymer (CFRP) composites are increasingly used in lightweight structures; however, their poor thermal conductivity poses challenges during drilling, where excessive heat degrades the epoxy matrix. This study investigates the individual and combined effects of wax (0–2%) as a solid lubricant and graphene nanoplatelets (0–2%) as a heat dissipation enhancer on cutting temperature during CFRP drilling. A data-driven modeling approach based on response surface methodology (RSM) with dummy variables was developed using a full factorial design comprising 225 unique experimental conditions (9 formulations × 5 cutting speeds × 5 feed rates) with three replicates per condition, resulting in 675 individual drilling tests. The RSM model was fitted to the 225 condition means. The global RSM model achieved high predictive accuracy (R2 = 0.9250, RMSE = 2.83 °C). Results show that increasing the feed rate reduces temperature by up to 29% and improves process stability, contrary to conventional metal cutting behavior. The addition of 2% wax reduced mean temperature by 11.3% and decreased thermal variability by 26%. Graphene exhibited an optimal concentration at 0.25%, yielding a 4.3% reduction in cutting temperature, with higher concentrations providing no additional benefit due to agglomeration. The combined effects of wax and graphene resulted in an optimal formulation containing 2% wax and 0.25% graphene, which provided the most favorable balance between low cutting temperature (46.1 °C) and enhanced thermal consistency (standard deviation = 3.53 °C). These findings provide practical guidelines for designing thermally regulated CFRP composites for high-performance drilling operations. 2026-08-01 JMMP, Vol. 10, Pages 275: Data-Driven Modeling of Thermal Regulation in CFRP Drilling: RSM-Based Combined Effects of Wax and Graphene Additives

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080275

Authors: Mohamed Slamani Chabha Kebaili Jean-François Chatelain

Carbon fiber-reinforced polymer (CFRP) composites are increasingly used in lightweight structures; however, their poor thermal conductivity poses challenges during drilling, where excessive heat degrades the epoxy matrix. This study investigates the individual and combined effects of wax (0–2%) as a solid lubricant and graphene nanoplatelets (0–2%) as a heat dissipation enhancer on cutting temperature during CFRP drilling. A data-driven modeling approach based on response surface methodology (RSM) with dummy variables was developed using a full factorial design comprising 225 unique experimental conditions (9 formulations × 5 cutting speeds × 5 feed rates) with three replicates per condition, resulting in 675 individual drilling tests. The RSM model was fitted to the 225 condition means. The global RSM model achieved high predictive accuracy (R2 = 0.9250, RMSE = 2.83 °C). Results show that increasing the feed rate reduces temperature by up to 29% and improves process stability, contrary to conventional metal cutting behavior. The addition of 2% wax reduced mean temperature by 11.3% and decreased thermal variability by 26%. Graphene exhibited an optimal concentration at 0.25%, yielding a 4.3% reduction in cutting temperature, with higher concentrations providing no additional benefit due to agglomeration. The combined effects of wax and graphene resulted in an optimal formulation containing 2% wax and 0.25% graphene, which provided the most favorable balance between low cutting temperature (46.1 °C) and enhanced thermal consistency (standard deviation = 3.53 °C). These findings provide practical guidelines for designing thermally regulated CFRP composites for high-performance drilling operations.

]]> Data-Driven Modeling of Thermal Regulation in CFRP Drilling: RSM-Based Combined Effects of Wax and Graphene Additives Mohamed Slamani Chabha Kebaili Jean-François Chatelain doi: 10.3390/jmmp10080275 Journal of Manufacturing and Materials Processing 2026-08-01 Journal of Manufacturing and Materials Processing 2026-08-01 10 8 Article 275 10.3390/jmmp10080275 https://www.mdpi.com/2504-4494/10/8/275 JMMP, Vol. 10, Pages 274: Evaluation of Structural and Phase Stability of Multi-Component Heat-Resistant Coatings Based on Alloyed Iron and Nickel Aluminides https://www.mdpi.com/2504-4494/10/8/274 This study investigates the synthesis, phase evolution, and high-temperature oxidation behavior of multi-component aluminide coatings on EP670 (Fe-Ni base), EP718 (Ni-Fe base), and EP648 (Ni-base) superalloys. The coatings were produced using an economical hot-dip aluminizing method, followed by diffusion heat treatment at 1100 °C. In the as-deposited state, the coatings exhibit a heterogeneous structure consisting of an aluminum matrix with various Al-rich intermetallic inclusions. Subsequent heat treatment promotes the redistribution of chemical elements, leading to the elimination of free aluminum and the stabilization of a protective β-phase matrix. Long-term oxidation tests were performed at 900 °C, 1100 °C, and 1300 °C for up to 1000 h. At 1100 °C, the coatings on EP670 and EP648 demonstrated high stability, following a near-parabolic oxidation law and significantly reducing mass gain compared to uncoated substrates. However, at 1100 °C, the EP718 alloy underwent catastrophic failure within 200 h due to pest oxidation, disintegrating into an oxide powder—a phenomenon quantitatively confirmed by the kinetic exponent dropping below 1.0. At 1300 °C, the thermal limit for all coatings was established, with protective properties failing after 50 h. Based on the aluminum depletion kinetics, the service life at 1100 °C was estimated at 1300 h for EP670 and 2200 h for EP648. Scratch testing confirmed a complete absence of interfacial adhesive cracks across all systems. Contact loading triggered only cohesive cracks localized within the near-surface zone of the coatings. The results highlight the superior thermodynamic compatibility of the EP670 and EP648 systems with aluminide coatings, making them the most suitable candidates for extreme high-temperature applications. 2026-08-01 JMMP, Vol. 10, Pages 274: Evaluation of Structural and Phase Stability of Multi-Component Heat-Resistant Coatings Based on Alloyed Iron and Nickel Aluminides

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080274

Authors: Vitaliy Pavlovich Kulevich Victor Georgievich Shmorgun Artem Igorevich Bogdanov Oleg Viktorovich Slautin Dmitriy Vladimirovich Pronichev Leonid Moiseevich Gurevich

This study investigates the synthesis, phase evolution, and high-temperature oxidation behavior of multi-component aluminide coatings on EP670 (Fe-Ni base), EP718 (Ni-Fe base), and EP648 (Ni-base) superalloys. The coatings were produced using an economical hot-dip aluminizing method, followed by diffusion heat treatment at 1100 °C. In the as-deposited state, the coatings exhibit a heterogeneous structure consisting of an aluminum matrix with various Al-rich intermetallic inclusions. Subsequent heat treatment promotes the redistribution of chemical elements, leading to the elimination of free aluminum and the stabilization of a protective β-phase matrix. Long-term oxidation tests were performed at 900 °C, 1100 °C, and 1300 °C for up to 1000 h. At 1100 °C, the coatings on EP670 and EP648 demonstrated high stability, following a near-parabolic oxidation law and significantly reducing mass gain compared to uncoated substrates. However, at 1100 °C, the EP718 alloy underwent catastrophic failure within 200 h due to pest oxidation, disintegrating into an oxide powder—a phenomenon quantitatively confirmed by the kinetic exponent dropping below 1.0. At 1300 °C, the thermal limit for all coatings was established, with protective properties failing after 50 h. Based on the aluminum depletion kinetics, the service life at 1100 °C was estimated at 1300 h for EP670 and 2200 h for EP648. Scratch testing confirmed a complete absence of interfacial adhesive cracks across all systems. Contact loading triggered only cohesive cracks localized within the near-surface zone of the coatings. The results highlight the superior thermodynamic compatibility of the EP670 and EP648 systems with aluminide coatings, making them the most suitable candidates for extreme high-temperature applications.

]]> Evaluation of Structural and Phase Stability of Multi-Component Heat-Resistant Coatings Based on Alloyed Iron and Nickel Aluminides Vitaliy Pavlovich Kulevich Victor Georgievich Shmorgun Artem Igorevich Bogdanov Oleg Viktorovich Slautin Dmitriy Vladimirovich Pronichev Leonid Moiseevich Gurevich doi: 10.3390/jmmp10080274 Journal of Manufacturing and Materials Processing 2026-08-01 Journal of Manufacturing and Materials Processing 2026-08-01 10 8 Article 274 10.3390/jmmp10080274 https://www.mdpi.com/2504-4494/10/8/274 JMMP, Vol. 10, Pages 273: From Industry 4.0 Readiness to Sustainable Manufacturing: An IMPULS-Informed PLS-SEM Analysis of Organisational and Technological Capabilities https://www.mdpi.com/2504-4494/10/8/273 The transition towards Industry 4.0 has significantly heightened the need for manufacturing firms to assess their organisational readiness for the digital transformation of production systems while aligning with sustainable manufacturing goals. Despite increasing scholarly attention to Industry 4.0, there is limited evidence of how organisational and technological capabilities, through readiness, translate into sustainable manufacturing outcomes in emerging economies such as Pakistan. This study addresses this gap by examining the relationships among the six IMPULS dimensions, namely strategy and organisation, smart factory, smart operations, smart product, data-driven services, and employees, together with additional organisational and technological readiness factors, Industry 4.0 readiness, and sustainable manufacturing in the context of Pakistani manufacturing firms. A quantitative cross-sectional design was used, while data were collected from 470 respondents across various manufacturing sectors using a structured questionnaire constructed on validated measurement scales. This study develops and empirically tests an extended IMPULS-informed readiness-to-sustainability framework that integrates established Industry 4.0 readiness dimensions with additional organisational and technological capability factors relevant to sustainable manufacturing. The study makes a methodological distinction by operationalising an IMPULS-informed framework that connects its six dimensions with Industry 4.0 readiness and sustainable manufacturing within a single empirical model. The proposed model was examined using partial least squares structural equation modelling (PLS-SEM). The findings reveal that strategy and organisation, employees, smart products, and smart operations substantially contribute to Industry 4.0 readiness. Conversely, smart factories and data-driven services do not have a significant direct impact on readiness. Sustainable manufacturing is strongly influenced by Industry 4.0 readiness, smart operations, and the smart factory. Mediation analysis further indicates that Industry 4.0 readiness serves as a significant transmission mechanism linking strategy and organisation, employees, smart products, and smart operations to sustainable manufacturing. The study extends the IMPULS framework by validating its relevance in an emerging economy and by demonstrating that sustainability gains from digital transformation rely more on coordinated organisational and operational readiness than on isolated technology adoption. The results provide evidence-based prioritisation guidance for managers and policymakers seeking to prioritise strategic alignment, workforce skills, and operational integration for successful, sustainable industrial transformation. 2026-08-01 JMMP, Vol. 10, Pages 273: From Industry 4.0 Readiness to Sustainable Manufacturing: An IMPULS-Informed PLS-SEM Analysis of Organisational and Technological Capabilities

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080273

Authors: Muhammad Adnan Javaid Butt Md. Ashikul Alam Khan Aamir Sohail Shrafat Ali Sair

The transition towards Industry 4.0 has significantly heightened the need for manufacturing firms to assess their organisational readiness for the digital transformation of production systems while aligning with sustainable manufacturing goals. Despite increasing scholarly attention to Industry 4.0, there is limited evidence of how organisational and technological capabilities, through readiness, translate into sustainable manufacturing outcomes in emerging economies such as Pakistan. This study addresses this gap by examining the relationships among the six IMPULS dimensions, namely strategy and organisation, smart factory, smart operations, smart product, data-driven services, and employees, together with additional organisational and technological readiness factors, Industry 4.0 readiness, and sustainable manufacturing in the context of Pakistani manufacturing firms. A quantitative cross-sectional design was used, while data were collected from 470 respondents across various manufacturing sectors using a structured questionnaire constructed on validated measurement scales. This study develops and empirically tests an extended IMPULS-informed readiness-to-sustainability framework that integrates established Industry 4.0 readiness dimensions with additional organisational and technological capability factors relevant to sustainable manufacturing. The study makes a methodological distinction by operationalising an IMPULS-informed framework that connects its six dimensions with Industry 4.0 readiness and sustainable manufacturing within a single empirical model. The proposed model was examined using partial least squares structural equation modelling (PLS-SEM). The findings reveal that strategy and organisation, employees, smart products, and smart operations substantially contribute to Industry 4.0 readiness. Conversely, smart factories and data-driven services do not have a significant direct impact on readiness. Sustainable manufacturing is strongly influenced by Industry 4.0 readiness, smart operations, and the smart factory. Mediation analysis further indicates that Industry 4.0 readiness serves as a significant transmission mechanism linking strategy and organisation, employees, smart products, and smart operations to sustainable manufacturing. The study extends the IMPULS framework by validating its relevance in an emerging economy and by demonstrating that sustainability gains from digital transformation rely more on coordinated organisational and operational readiness than on isolated technology adoption. The results provide evidence-based prioritisation guidance for managers and policymakers seeking to prioritise strategic alignment, workforce skills, and operational integration for successful, sustainable industrial transformation.

]]> From Industry 4.0 Readiness to Sustainable Manufacturing: An IMPULS-Informed PLS-SEM Analysis of Organisational and Technological Capabilities Muhammad Adnan Javaid Butt Md. Ashikul Alam Khan Aamir Sohail Shrafat Ali Sair doi: 10.3390/jmmp10080273 Journal of Manufacturing and Materials Processing 2026-08-01 Journal of Manufacturing and Materials Processing 2026-08-01 10 8 Article 273 10.3390/jmmp10080273 https://www.mdpi.com/2504-4494/10/8/273 JMMP, Vol. 10, Pages 272: From Rotary Burnishing Parameters to Joint Stiffness: A Two-Level Model for Surfaces with Regular Dimples https://www.mdpi.com/2504-4494/10/8/272 Normal contact stiffness is a key property of mechanical surface joints because it governs load transfer, local approach, vibration response, and positioning stability. Rotary burnishing can generate regular dimple patterns without superimposed tool vibration; however, existing process models mainly describe texture geometry and surface-layer modification rather than the mapping from burnishing parameters to normal joint stiffness. This paper develops a two-level semi-analytical model that couples deterministic dimple geometry and load redistribution with a Greenwood–Williamson-type response of the load-bearing land. The main geometrical and contact contributions are expressed explicitly, whereas the spectral summation, micro-roughness quadrature, and nonlinear closure are evaluated numerically. The process parameters define the nominal unit-cell geometry, whereas the residual dimple dimensions and measured post-burnishing descriptors are post-burnishing inputs. Published data for related regular microreliefs are used to benchmark the predicted trends and order of magnitude. For the reference regime, the explicit spectral displacement remains below 1% of the micro-roughness contribution. Periodic BEM predicts an additional approach 14–15% lower than the analytical term, while pressure heterogeneity changes the averaged micro-roughness approach by less than 1.7%. The model is also used for sensitivity analysis and inverse design of rotary-burnishing parameters to generate design maps for preliminary process selection. Within the stated validity domain, the model serves as a fast screening tool for the stabilized repeated-loading stiffness of dimpled joints. 2026-07-31 JMMP, Vol. 10, Pages 272: From Rotary Burnishing Parameters to Joint Stiffness: A Two-Level Model for Surfaces with Regular Dimples

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080272

Authors: Kirill A. Bashmur Alexander V. Zagulyaev

Normal contact stiffness is a key property of mechanical surface joints because it governs load transfer, local approach, vibration response, and positioning stability. Rotary burnishing can generate regular dimple patterns without superimposed tool vibration; however, existing process models mainly describe texture geometry and surface-layer modification rather than the mapping from burnishing parameters to normal joint stiffness. This paper develops a two-level semi-analytical model that couples deterministic dimple geometry and load redistribution with a Greenwood–Williamson-type response of the load-bearing land. The main geometrical and contact contributions are expressed explicitly, whereas the spectral summation, micro-roughness quadrature, and nonlinear closure are evaluated numerically. The process parameters define the nominal unit-cell geometry, whereas the residual dimple dimensions and measured post-burnishing descriptors are post-burnishing inputs. Published data for related regular microreliefs are used to benchmark the predicted trends and order of magnitude. For the reference regime, the explicit spectral displacement remains below 1% of the micro-roughness contribution. Periodic BEM predicts an additional approach 14–15% lower than the analytical term, while pressure heterogeneity changes the averaged micro-roughness approach by less than 1.7%. The model is also used for sensitivity analysis and inverse design of rotary-burnishing parameters to generate design maps for preliminary process selection. Within the stated validity domain, the model serves as a fast screening tool for the stabilized repeated-loading stiffness of dimpled joints.

]]> From Rotary Burnishing Parameters to Joint Stiffness: A Two-Level Model for Surfaces with Regular Dimples Kirill A. Bashmur Alexander V. Zagulyaev doi: 10.3390/jmmp10080272 Journal of Manufacturing and Materials Processing 2026-07-31 Journal of Manufacturing and Materials Processing 2026-07-31 10 8 Article 272 10.3390/jmmp10080272 https://www.mdpi.com/2504-4494/10/8/272 JMMP, Vol. 10, Pages 271: Different Plasma Polishing Regimes Induced by Electrolytic Flow https://www.mdpi.com/2504-4494/10/8/271 This study investigates electrolyte jet processing of metals by plasma polishing, focusing on the polishing regimes and their governing flow dynamics, which result in different current density distributions and, consequently, different plasma polishing regimes. Experimental investigations performed at 350 V using a fixed-diameter electrolyte jet included localized current measurements and surface topography characterization, while finite element method (FEM) simulations were used to evaluate four plasma vapor–gas envelope (VGE) geometries. The experimental results revealed two distinct polishing regimes: a contact zone coinciding with the nozzle diameter, where the highest local cur-rent density reached 10.8 mA/mm2 and produced a maximum material removal rate of 1.17 µm/s, and a surrounding electrolyte splash zone extending to approximately twice the nozzle diameter, where the local current density progressively decreased to 2.6 mA/mm2, corresponding to a minimum material removal rate of 0.16 µm/s. Unlike previous, studies the numerical simulations showed that a constant plasma vapor–gas envelope thickness of 15.8 µm provided the closest agreement with the experimentally measured polishing profile. Based on the combined experimental and numerical results, the contact zone is interpreted as a plasma-dominated region characterized by high current density, whereas the splash zone is interpreted as a transient plasma regime in which electrochemical polishing increasingly dominates as current density decreases. This study improves the understanding of plasma electrolyte polishing (PEP), which involves both plasma-assisted and electrochemical material-removal mechanisms. The results provide guidance for im-proving surface quality and process efficiency in electrolyte-jet PEP of stainless steel. 2026-07-31 JMMP, Vol. 10, Pages 271: Different Plasma Polishing Regimes Induced by Electrolytic Flow

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080271

Authors: Adel Ghezri Yan Scholl Nick Huber Killang Pratama Thomas Nelis Jürgen Burger Cedric Bessire

This study investigates electrolyte jet processing of metals by plasma polishing, focusing on the polishing regimes and their governing flow dynamics, which result in different current density distributions and, consequently, different plasma polishing regimes. Experimental investigations performed at 350 V using a fixed-diameter electrolyte jet included localized current measurements and surface topography characterization, while finite element method (FEM) simulations were used to evaluate four plasma vapor–gas envelope (VGE) geometries. The experimental results revealed two distinct polishing regimes: a contact zone coinciding with the nozzle diameter, where the highest local cur-rent density reached 10.8 mA/mm2 and produced a maximum material removal rate of 1.17 µm/s, and a surrounding electrolyte splash zone extending to approximately twice the nozzle diameter, where the local current density progressively decreased to 2.6 mA/mm2, corresponding to a minimum material removal rate of 0.16 µm/s. Unlike previous, studies the numerical simulations showed that a constant plasma vapor–gas envelope thickness of 15.8 µm provided the closest agreement with the experimentally measured polishing profile. Based on the combined experimental and numerical results, the contact zone is interpreted as a plasma-dominated region characterized by high current density, whereas the splash zone is interpreted as a transient plasma regime in which electrochemical polishing increasingly dominates as current density decreases. This study improves the understanding of plasma electrolyte polishing (PEP), which involves both plasma-assisted and electrochemical material-removal mechanisms. The results provide guidance for im-proving surface quality and process efficiency in electrolyte-jet PEP of stainless steel.

]]> Different Plasma Polishing Regimes Induced by Electrolytic Flow Adel Ghezri Yan Scholl Nick Huber Killang Pratama Thomas Nelis Jürgen Burger Cedric Bessire doi: 10.3390/jmmp10080271 Journal of Manufacturing and Materials Processing 2026-07-31 Journal of Manufacturing and Materials Processing 2026-07-31 10 8 Article 271 10.3390/jmmp10080271 https://www.mdpi.com/2504-4494/10/8/271 JMMP, Vol. 10, Pages 270: An Innovative Self-Adaptive Expert System for Improving Energy Efficiency in Cement Mill Grinding Operation https://www.mdpi.com/2504-4494/10/8/270 The cement industry, responsible for 26% of industrial CO2 emissions and 8% of global emissions, is under growing pressure to reduce its environmental footprint while maintaining profitability. In this context, optimizing grinding processes is essential to enhance both the efficiency and sustainability of cement production. This study presents the development of a self-adaptive expert system for closed-loop control, integrating symbolic Artificial Intelligence (AI) and Advanced Process Control (APC) techniques. The system dynamically adjusts operational parameters in real time to minimize the specific energy consumption of cement grinding while meeting quality targets. Notably, it enables autonomous plant operation without direct human supervision, thereby reallocating personnel to higher-value tasks and maintaining optimal performance continuously. The benefits observed following industrial implementation are discussed, alongside an analysis of the key factors influencing grinding performance and productivity. Furthermore, the integration of Artificial Neural Networks (ANNs) and genetic algorithms is proposed as a future enhancement, complementing the expert system through neuro-symbolic approaches. This fusion represents a significant step toward the digital transformation of industrial operations. 2026-07-29 JMMP, Vol. 10, Pages 270: An Innovative Self-Adaptive Expert System for Improving Energy Efficiency in Cement Mill Grinding Operation

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080270

Authors: Raimundo Fernández Gassó Lorenzo Sevilla Hurtado Juan Miguel Cañero-Nieto

The cement industry, responsible for 26% of industrial CO2 emissions and 8% of global emissions, is under growing pressure to reduce its environmental footprint while maintaining profitability. In this context, optimizing grinding processes is essential to enhance both the efficiency and sustainability of cement production. This study presents the development of a self-adaptive expert system for closed-loop control, integrating symbolic Artificial Intelligence (AI) and Advanced Process Control (APC) techniques. The system dynamically adjusts operational parameters in real time to minimize the specific energy consumption of cement grinding while meeting quality targets. Notably, it enables autonomous plant operation without direct human supervision, thereby reallocating personnel to higher-value tasks and maintaining optimal performance continuously. The benefits observed following industrial implementation are discussed, alongside an analysis of the key factors influencing grinding performance and productivity. Furthermore, the integration of Artificial Neural Networks (ANNs) and genetic algorithms is proposed as a future enhancement, complementing the expert system through neuro-symbolic approaches. This fusion represents a significant step toward the digital transformation of industrial operations.

]]> An Innovative Self-Adaptive Expert System for Improving Energy Efficiency in Cement Mill Grinding Operation Raimundo Fernández Gassó Lorenzo Sevilla Hurtado Juan Miguel Cañero-Nieto doi: 10.3390/jmmp10080270 Journal of Manufacturing and Materials Processing 2026-07-29 Journal of Manufacturing and Materials Processing 2026-07-29 10 8 Article 270 10.3390/jmmp10080270 https://www.mdpi.com/2504-4494/10/8/270 JMMP, Vol. 10, Pages 269: Microstructure Validation of Graph Theory Model-Derived Cooling Rates in the Wire Arc Additive Manufacturing of ER70S-6 Steel https://www.mdpi.com/2504-4494/10/8/269 Wire arc additive manufacturing (WAAM) enables high-rate fabrication of large metallic components, but spatial variations in thermal history can lead to microstructural heterogeneity that requires efficient process models to evaluate. This study evaluates whether cooling rates extracted from a graph theory model (GTM)-based thermal simulation are consistent with the microstructural evolution observed in an ER70S-6 WAAM wall. Thermal histories from the model were analyzed at selected build heights, and cooling rates were extracted from the final thermal excursion through the austenite phase field. Microstructures at corresponding locations were characterized using electron backscatter diffraction (EBSD) to quantify grain size distributions, and pearlite interlamellar spacing was used as an additional indicator of cooling behavior. The modeled cooling rates were highest near the substrate and generally decreased with build height, consistent with the observed reduction in the fine grain fraction and the progressive shift in the grain size distribution as build height increased. Pearlite spacing trends also supported the modeled cooling rate variation. These results indicate that GTM-derived thermal histories can be post-processed into metallurgically meaningful cooling rate estimates for WAAM steel builds and linked to dataset specific empirical grain size distribution relationships for process–thermal history–microstructure assessment. 2026-07-28 JMMP, Vol. 10, Pages 269: Microstructure Validation of Graph Theory Model-Derived Cooling Rates in the Wire Arc Additive Manufacturing of ER70S-6 Steel

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080269

Authors: Mark Anderson Nicholas Piercy Kevin Cole Prahalada Rao Simhambhatla Suryakumar Jeffrey E. Shield

Wire arc additive manufacturing (WAAM) enables high-rate fabrication of large metallic components, but spatial variations in thermal history can lead to microstructural heterogeneity that requires efficient process models to evaluate. This study evaluates whether cooling rates extracted from a graph theory model (GTM)-based thermal simulation are consistent with the microstructural evolution observed in an ER70S-6 WAAM wall. Thermal histories from the model were analyzed at selected build heights, and cooling rates were extracted from the final thermal excursion through the austenite phase field. Microstructures at corresponding locations were characterized using electron backscatter diffraction (EBSD) to quantify grain size distributions, and pearlite interlamellar spacing was used as an additional indicator of cooling behavior. The modeled cooling rates were highest near the substrate and generally decreased with build height, consistent with the observed reduction in the fine grain fraction and the progressive shift in the grain size distribution as build height increased. Pearlite spacing trends also supported the modeled cooling rate variation. These results indicate that GTM-derived thermal histories can be post-processed into metallurgically meaningful cooling rate estimates for WAAM steel builds and linked to dataset specific empirical grain size distribution relationships for process–thermal history–microstructure assessment.

]]> Microstructure Validation of Graph Theory Model-Derived Cooling Rates in the Wire Arc Additive Manufacturing of ER70S-6 Steel Mark Anderson Nicholas Piercy Kevin Cole Prahalada Rao Simhambhatla Suryakumar Jeffrey E. Shield doi: 10.3390/jmmp10080269 Journal of Manufacturing and Materials Processing 2026-07-28 Journal of Manufacturing and Materials Processing 2026-07-28 10 8 Article 269 10.3390/jmmp10080269 https://www.mdpi.com/2504-4494/10/8/269 JMMP, Vol. 10, Pages 268: Enabling Bulk High-Temperature Additive Friction Stir Deposition of Steels with Polycrystalline Cubic Boron Nitride-Based Tools https://www.mdpi.com/2504-4494/10/8/268 Forgings currently have long lead times, motivating technology developments that produce parts with forge-like properties and have shorter timelines. Solid-state processes such as additive friction stir deposition (AFSD) offer this potential; however, large-scale deposition of high-temperature materials remains limited by tool durability, thermal management, and process stability. In this study, new polycrystalline cubic boron nitride (PCBN) AFSD tools, integrated with a liquid-cooled tool holder, are developed and evaluated for bulk deposition of 316 L stainless steel. Tool geometry modifications, including increased puck diameter and a drafted feed exit orifice, enabled graphite-free deposition by mitigating feedstock swaging. A minimum deposition rate is identified that maintains stable material flow and avoids excessive actuator forces. Comparing the use of PCBN tools with different shank materials shows that tungsten carbide shanked tools have improved thermal management relative to tools with a nickel-based shank. This improved thermal regulation resulted in more stable deposition, reduced tool wear, and successful multi-layer builds. Additionally, the use of a fully enclosed inert gas environment reduces surface oxidation and interlayer oxide formation. Electron microscopy was used to reveal limited tool-related contamination in the deposition. The contamination observed was dispersed boron nitride particles rather than continuous interfacial layers of tool material as observed in other literature. These results demonstrate that PCBN tooling combined with active cooling can enable stable, bulk AFSD of high-temperature alloys. 2026-07-28 JMMP, Vol. 10, Pages 268: Enabling Bulk High-Temperature Additive Friction Stir Deposition of Steels with Polycrystalline Cubic Boron Nitride-Based Tools

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080268

Authors: Luk Dean Brian Gierk Jason Stewart Kaj Call Carl Schmidt Yuri Hovanski

Forgings currently have long lead times, motivating technology developments that produce parts with forge-like properties and have shorter timelines. Solid-state processes such as additive friction stir deposition (AFSD) offer this potential; however, large-scale deposition of high-temperature materials remains limited by tool durability, thermal management, and process stability. In this study, new polycrystalline cubic boron nitride (PCBN) AFSD tools, integrated with a liquid-cooled tool holder, are developed and evaluated for bulk deposition of 316 L stainless steel. Tool geometry modifications, including increased puck diameter and a drafted feed exit orifice, enabled graphite-free deposition by mitigating feedstock swaging. A minimum deposition rate is identified that maintains stable material flow and avoids excessive actuator forces. Comparing the use of PCBN tools with different shank materials shows that tungsten carbide shanked tools have improved thermal management relative to tools with a nickel-based shank. This improved thermal regulation resulted in more stable deposition, reduced tool wear, and successful multi-layer builds. Additionally, the use of a fully enclosed inert gas environment reduces surface oxidation and interlayer oxide formation. Electron microscopy was used to reveal limited tool-related contamination in the deposition. The contamination observed was dispersed boron nitride particles rather than continuous interfacial layers of tool material as observed in other literature. These results demonstrate that PCBN tooling combined with active cooling can enable stable, bulk AFSD of high-temperature alloys.

]]> Enabling Bulk High-Temperature Additive Friction Stir Deposition of Steels with Polycrystalline Cubic Boron Nitride-Based Tools Luk Dean Brian Gierk Jason Stewart Kaj Call Carl Schmidt Yuri Hovanski doi: 10.3390/jmmp10080268 Journal of Manufacturing and Materials Processing 2026-07-28 Journal of Manufacturing and Materials Processing 2026-07-28 10 8 Article 268 10.3390/jmmp10080268 https://www.mdpi.com/2504-4494/10/8/268 JMMP, Vol. 10, Pages 267: Additive Manufacturing of Functionally Graded Lattice Structures: Process–Structure–Property Relationships, Design Strategies, and Future Perspectives https://www.mdpi.com/2504-4494/10/8/267 Functionally graded lattice structures (FGLSs) have emerged as a promising class of architected materials that enable spatial control of mechanical, thermal, and biological properties through variations in geometry, topology, material composition, and density. Advances in additive manufacturing (AM) have significantly expanded the design and fabrication capabilities of FGLSs for applications in aerospace, biomedical, energy, and transportation sectors. This review presents a comprehensive assessment of FGLSs through a process–structure–property (P–S–P) perspective, highlighting the influence of AM processes, manufacturing defects, and microstructural evolution on structural performance. A unified six-axis taxonomy (topology family, graded variable, gradient-field description, scale level, process and material route, target metric) is proposed for cross-study comparison. Five architecture families are examined: strut-based, triply periodic minimal surface (TPMS), stochastic, plate-based, and mechanism-driven or hierarchical lattices, together with density, material, topology, and hybrid grading approaches. Recent advances in computational modeling, topology optimization, artificial intelligence (AI), and machine learning are discussed, emphasizing their role in accelerating design, property prediction, and inverse engineering. Finally, key challenges and future opportunities related to digital twins, autonomous manufacturing, multi-material systems, and qualification of FGLSs are identified. This review provides a structured framework for the development of next-generation AI-enabled FGLSs with enhanced multifunctional performance and manufacturability. 2026-07-27 JMMP, Vol. 10, Pages 267: Additive Manufacturing of Functionally Graded Lattice Structures: Process–Structure–Property Relationships, Design Strategies, and Future Perspectives

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080267

Authors: Abdulcelil Bayar Fatih Altun Ahmet Enes Sarac Saleh Ateiwi Seyda Naz Alasahin Eylem Asmatulu

Functionally graded lattice structures (FGLSs) have emerged as a promising class of architected materials that enable spatial control of mechanical, thermal, and biological properties through variations in geometry, topology, material composition, and density. Advances in additive manufacturing (AM) have significantly expanded the design and fabrication capabilities of FGLSs for applications in aerospace, biomedical, energy, and transportation sectors. This review presents a comprehensive assessment of FGLSs through a process–structure–property (P–S–P) perspective, highlighting the influence of AM processes, manufacturing defects, and microstructural evolution on structural performance. A unified six-axis taxonomy (topology family, graded variable, gradient-field description, scale level, process and material route, target metric) is proposed for cross-study comparison. Five architecture families are examined: strut-based, triply periodic minimal surface (TPMS), stochastic, plate-based, and mechanism-driven or hierarchical lattices, together with density, material, topology, and hybrid grading approaches. Recent advances in computational modeling, topology optimization, artificial intelligence (AI), and machine learning are discussed, emphasizing their role in accelerating design, property prediction, and inverse engineering. Finally, key challenges and future opportunities related to digital twins, autonomous manufacturing, multi-material systems, and qualification of FGLSs are identified. This review provides a structured framework for the development of next-generation AI-enabled FGLSs with enhanced multifunctional performance and manufacturability.

]]> Additive Manufacturing of Functionally Graded Lattice Structures: Process–Structure–Property Relationships, Design Strategies, and Future Perspectives Abdulcelil Bayar Fatih Altun Ahmet Enes Sarac Saleh Ateiwi Seyda Naz Alasahin Eylem Asmatulu doi: 10.3390/jmmp10080267 Journal of Manufacturing and Materials Processing 2026-07-27 Journal of Manufacturing and Materials Processing 2026-07-27 10 8 Review 267 10.3390/jmmp10080267 https://www.mdpi.com/2504-4494/10/8/267 JMMP, Vol. 10, Pages 266: Mechanical Testing of Polyethylene Terephthalate Glycol Processed with Fused Deposition Modelling https://www.mdpi.com/2504-4494/10/8/266 Polyethylene Terephthalate Glycol (PETG) is a thermoplastic material used in Fused Deposition Modelling for prosthetic applications, where mechanical properties are strongly dependent on process parameters. This study investigated the effects of carbon fibre (CF) content, print orientation (PO), and print temperature (PT) on the mechanical performance of PETG, fabricated using a Bambu Lab A1 printer. Tensile, three-point bending and impact testing were conducted to characterise the mechanical response of printed specimens. A Taguchi L9 array was employed to evaluate parameter effects while minimising experimental runs, and factor effects were quantified using per-response general linear models. Findings indicated that PO and PT significantly affected tensile behaviour, while CF content dominated flexural stiffness and impact response, with the strongest tensile response at 240 °C attributed to improved interlayer bonding. CF reinforcement increased stiffness and flexural strength but had limited effect on tensile strength and a reduced impact resistance at higher loadings, indicating increased brittleness. PO was identified as the most influential factor, with upright specimens exhibiting superior tensile performance, consistent with more favourable alignment of filament deposition with the loading direction. These findings demonstrate that the mechanical behaviour of CF-PETG is strongly process-dependent, informing its future application within prosthetic limb design. 2026-07-27 JMMP, Vol. 10, Pages 266: Mechanical Testing of Polyethylene Terephthalate Glycol Processed with Fused Deposition Modelling

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080266

Authors: Zoe Wakefield Christian A. Griffiths Talitha D. de Wet Andrew J. Thomas

Polyethylene Terephthalate Glycol (PETG) is a thermoplastic material used in Fused Deposition Modelling for prosthetic applications, where mechanical properties are strongly dependent on process parameters. This study investigated the effects of carbon fibre (CF) content, print orientation (PO), and print temperature (PT) on the mechanical performance of PETG, fabricated using a Bambu Lab A1 printer. Tensile, three-point bending and impact testing were conducted to characterise the mechanical response of printed specimens. A Taguchi L9 array was employed to evaluate parameter effects while minimising experimental runs, and factor effects were quantified using per-response general linear models. Findings indicated that PO and PT significantly affected tensile behaviour, while CF content dominated flexural stiffness and impact response, with the strongest tensile response at 240 °C attributed to improved interlayer bonding. CF reinforcement increased stiffness and flexural strength but had limited effect on tensile strength and a reduced impact resistance at higher loadings, indicating increased brittleness. PO was identified as the most influential factor, with upright specimens exhibiting superior tensile performance, consistent with more favourable alignment of filament deposition with the loading direction. These findings demonstrate that the mechanical behaviour of CF-PETG is strongly process-dependent, informing its future application within prosthetic limb design.

]]> Mechanical Testing of Polyethylene Terephthalate Glycol Processed with Fused Deposition Modelling Zoe Wakefield Christian A. Griffiths Talitha D. de Wet Andrew J. Thomas doi: 10.3390/jmmp10080266 Journal of Manufacturing and Materials Processing 2026-07-27 Journal of Manufacturing and Materials Processing 2026-07-27 10 8 Article 266 10.3390/jmmp10080266 https://www.mdpi.com/2504-4494/10/8/266 JMMP, Vol. 10, Pages 265: Scale-Dependent GD&T Conformity and Surface Roughness in PLA Parts Manufactured by Material Extrusion: A Metrological Assessment https://www.mdpi.com/2504-4494/10/8/265 Dimensional accuracy and surface roughness in material extrusion (MEX) have been widely studied; however, the effect of part scale on the simultaneous fulfilment of geometrical tolerances and surface finish remains less clearly established. This study evaluates the scale-dependent quality of PLA parts manufactured by material extrusion (MEX) using a full 3 × 3 × 3 factorial design, combining three scales (1×, 0.75×, and 0.5×), three commercial PLA filaments, and three printing speeds (40, 60, and 80 mm/s). A dedicated test artefact was inspected by a coordinate measuring machine to quantify GD&T-related deviations, including flatness, perpendicularity, parallelism, angularity, circularity, cylindricity, and coaxiality. Surface roughness was characterized by 2D profilometry using Ra, Rz, and Rq on representative horizontal and vertical surfaces. Results showed that part scale was the dominant factor affecting geometrical conformity, especially for orientation- and location-related tolerances such as perpendicularity, parallelism, and coaxiality, which deteriorated markedly as specimen size decreased. Filament type also influenced several geometrical responses, whereas printing speed showed no significant main effect on geometrical tolerances within the evaluated range. Surface roughness exhibited clear anisotropy, with vertical surfaces showing higher values and stronger statistical dependence on process factors. Unlike studies focused only on dimensional accuracy or surface roughness, this work provides an integrated GD&T-based and surface-texture assessment of scale-dependent quality loss in PLA parts manufactured by MEX. These findings may help designers and manufacturers define inspection criteria, select suitable commercial PLA filaments, and identify critical geometrical features when scaled MEX parts are intended for functional applications. 2026-07-27 JMMP, Vol. 10, Pages 265: Scale-Dependent GD&T Conformity and Surface Roughness in PLA Parts Manufactured by Material Extrusion: A Metrological Assessment

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080265

Authors: Guillermo Guerrero-Vacas Gustavo Marcelo Flores Daniel Caballero Arturo Valle-Cobos Óscar Rodríguez-Alabanda

Dimensional accuracy and surface roughness in material extrusion (MEX) have been widely studied; however, the effect of part scale on the simultaneous fulfilment of geometrical tolerances and surface finish remains less clearly established. This study evaluates the scale-dependent quality of PLA parts manufactured by material extrusion (MEX) using a full 3 × 3 × 3 factorial design, combining three scales (1×, 0.75×, and 0.5×), three commercial PLA filaments, and three printing speeds (40, 60, and 80 mm/s). A dedicated test artefact was inspected by a coordinate measuring machine to quantify GD&T-related deviations, including flatness, perpendicularity, parallelism, angularity, circularity, cylindricity, and coaxiality. Surface roughness was characterized by 2D profilometry using Ra, Rz, and Rq on representative horizontal and vertical surfaces. Results showed that part scale was the dominant factor affecting geometrical conformity, especially for orientation- and location-related tolerances such as perpendicularity, parallelism, and coaxiality, which deteriorated markedly as specimen size decreased. Filament type also influenced several geometrical responses, whereas printing speed showed no significant main effect on geometrical tolerances within the evaluated range. Surface roughness exhibited clear anisotropy, with vertical surfaces showing higher values and stronger statistical dependence on process factors. Unlike studies focused only on dimensional accuracy or surface roughness, this work provides an integrated GD&T-based and surface-texture assessment of scale-dependent quality loss in PLA parts manufactured by MEX. These findings may help designers and manufacturers define inspection criteria, select suitable commercial PLA filaments, and identify critical geometrical features when scaled MEX parts are intended for functional applications.

]]> Scale-Dependent GD&T Conformity and Surface Roughness in PLA Parts Manufactured by Material Extrusion: A Metrological Assessment Guillermo Guerrero-Vacas Gustavo Marcelo Flores Daniel Caballero Arturo Valle-Cobos Óscar Rodríguez-Alabanda doi: 10.3390/jmmp10080265 Journal of Manufacturing and Materials Processing 2026-07-27 Journal of Manufacturing and Materials Processing 2026-07-27 10 8 Article 265 10.3390/jmmp10080265 https://www.mdpi.com/2504-4494/10/8/265 JMMP, Vol. 10, Pages 264: Defect-Sensitivity Analysis of Yield Behavior in Additively Manufactured 316L Stainless-Steel Pipe Material Using a Monte Carlo-Reconstructed Crystal Plasticity Finite Element Model https://www.mdpi.com/2504-4494/10/8/264 Defects such as lack-of-fusion pores, keyhole pores, and thermal cracks are inherent to additively manufactured (AM) components and significantly degrade their mechanical performance, yet their quantitative influence on the strength of AM structures remains insufficiently understood. In this study, a columnar-grained microstructure of AM 316L stainless-steel pipe material containing explicit pores and cracks was reconstructed using the Monte Carlo method based on SEM observations and was incorporated into a calibrated crystal plasticity finite element model. The reconstructed columnar-grain width agreed with the measured value, and the predicted yield strengths of both defect-free and defect-containing material matched tensile measurements, confirming the accuracy of the micromechanical framework. Moreover, the influences of the pore diameter, crack length, pore arrangement, and porosity on the circumferential and axial yielding were systematically investigated. Results showed that increasing the size of the pore and porosity reduced the circumferential and axial yield strengths simultaneously with distinct extents. Cracks exhibited pronounced directional sensitivity: circumferential cracks mainly reduced axial capacity, whereas an axial crack reduced circumferential strength significantly, indicating that crack-induced degradation is governed by the interaction between crack orientation and loading direction. Directional pore arrangements produced anisotropic responses, whereas random arrangements reduced this anisotropy and resulted in a quasi-isotropic response, although clustering at higher porosity intensified local stress-concentration interactions and further lowered load-bearing capacity. The results clarify the mechanisms of defect-induced stress concentration and local plastic evolution and provide a quantitative basis for defect-tolerance assessment and quality control of AM components. 2026-07-24 JMMP, Vol. 10, Pages 264: Defect-Sensitivity Analysis of Yield Behavior in Additively Manufactured 316L Stainless-Steel Pipe Material Using a Monte Carlo-Reconstructed Crystal Plasticity Finite Element Model

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080264

Authors: Hui Li Kejian Zhu Mingda Yu Yunzheng Gao Qi Wu Huayuan Tang

Defects such as lack-of-fusion pores, keyhole pores, and thermal cracks are inherent to additively manufactured (AM) components and significantly degrade their mechanical performance, yet their quantitative influence on the strength of AM structures remains insufficiently understood. In this study, a columnar-grained microstructure of AM 316L stainless-steel pipe material containing explicit pores and cracks was reconstructed using the Monte Carlo method based on SEM observations and was incorporated into a calibrated crystal plasticity finite element model. The reconstructed columnar-grain width agreed with the measured value, and the predicted yield strengths of both defect-free and defect-containing material matched tensile measurements, confirming the accuracy of the micromechanical framework. Moreover, the influences of the pore diameter, crack length, pore arrangement, and porosity on the circumferential and axial yielding were systematically investigated. Results showed that increasing the size of the pore and porosity reduced the circumferential and axial yield strengths simultaneously with distinct extents. Cracks exhibited pronounced directional sensitivity: circumferential cracks mainly reduced axial capacity, whereas an axial crack reduced circumferential strength significantly, indicating that crack-induced degradation is governed by the interaction between crack orientation and loading direction. Directional pore arrangements produced anisotropic responses, whereas random arrangements reduced this anisotropy and resulted in a quasi-isotropic response, although clustering at higher porosity intensified local stress-concentration interactions and further lowered load-bearing capacity. The results clarify the mechanisms of defect-induced stress concentration and local plastic evolution and provide a quantitative basis for defect-tolerance assessment and quality control of AM components.

]]> Defect-Sensitivity Analysis of Yield Behavior in Additively Manufactured 316L Stainless-Steel Pipe Material Using a Monte Carlo-Reconstructed Crystal Plasticity Finite Element Model Hui Li Kejian Zhu Mingda Yu Yunzheng Gao Qi Wu Huayuan Tang doi: 10.3390/jmmp10080264 Journal of Manufacturing and Materials Processing 2026-07-24 Journal of Manufacturing and Materials Processing 2026-07-24 10 8 Article 264 10.3390/jmmp10080264 https://www.mdpi.com/2504-4494/10/8/264 JMMP, Vol. 10, Pages 263: Transient Characterization and Feedforward Compensation in Fused Granular Fabrication Using Post-Consumer Recycled and Wood-Filled Polypropylenes https://www.mdpi.com/2504-4494/10/8/263 Transient extrusion defects are a fundamental process control challenge in fused granular fabrication (FGF), arising from the finite melt pressurization time of screw-driven extruders at each start–stop event. This study presents an integrated experimental and analytical framework for the characterization and open-loop feedforward compensation of these transient dynamics, demonstrated on two composite thermoplastic feedstocks: a recycled random polypropylene (RPP1) and a 20 wt% wood-fiber-reinforced polypropylene composite (WFPP). Unlike prior filament- or single-material feedforward strategies, this framework derives and statistically validates material-specific compensation parameters across two rheologically distinct feedstocks. Single-layer road experiments were conducted on a custom instrumented FGF platform across a 23−1 half-fraction factorial design varying melt temperature, print acceleration, and nozzle diameter, with screw speed stepped among 20, 40, and 80 RPM to excite transient states; deposited road geometry was digitized and spatially registered to the synchronized process signals. Main-effects regression confirmed that nozzle diameter is the dominant predictor of mean road width, while screw velocity exerts a significant negative effect attributable to speed-dependent backflow. Prediction-error minimization on the pooled multi-experiment dataset yielded a parsimonious first-order transfer function, G(s) = 0.990/(1 + 1.909s), whose time constant is physically attributed to melt compressibility in the barrel volume upstream of the nozzle restriction. This model was embedded in a G-code post-processor implementing two sequential corrections: a material-specific steady-state slip gain and a discrete linear-advance term parameterized by the identified time constant. For RPP1 at the nominal gain, the print latency interquartile range decreased from 5–20 mm to 2–8 mm without degrading steady-state dimensional accuracy; the combination of nominal gain with active retraction further reduced latency to near-zero. Analysis of covariance (ANCOVA) confirmed that optimal feedforward gains are statistically material-dependent across all three quality metrics (p < 0.05), providing statistical justification for material-specific compensator parameterization. The results establish a practical, hardware-agnostic route to reduce transient deposition defects in pellet-based additive manufacturing, extensible to additional feedstocks. 2026-07-23 JMMP, Vol. 10, Pages 263: Transient Characterization and Feedforward Compensation in Fused Granular Fabrication Using Post-Consumer Recycled and Wood-Filled Polypropylenes

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080263

Authors: Stiven Kodra David O. Kazmer Mitchell Mashburn Eric Gohl Patrick Ferrell

Transient extrusion defects are a fundamental process control challenge in fused granular fabrication (FGF), arising from the finite melt pressurization time of screw-driven extruders at each start–stop event. This study presents an integrated experimental and analytical framework for the characterization and open-loop feedforward compensation of these transient dynamics, demonstrated on two composite thermoplastic feedstocks: a recycled random polypropylene (RPP1) and a 20 wt% wood-fiber-reinforced polypropylene composite (WFPP). Unlike prior filament- or single-material feedforward strategies, this framework derives and statistically validates material-specific compensation parameters across two rheologically distinct feedstocks. Single-layer road experiments were conducted on a custom instrumented FGF platform across a 23−1 half-fraction factorial design varying melt temperature, print acceleration, and nozzle diameter, with screw speed stepped among 20, 40, and 80 RPM to excite transient states; deposited road geometry was digitized and spatially registered to the synchronized process signals. Main-effects regression confirmed that nozzle diameter is the dominant predictor of mean road width, while screw velocity exerts a significant negative effect attributable to speed-dependent backflow. Prediction-error minimization on the pooled multi-experiment dataset yielded a parsimonious first-order transfer function, G(s) = 0.990/(1 + 1.909s), whose time constant is physically attributed to melt compressibility in the barrel volume upstream of the nozzle restriction. This model was embedded in a G-code post-processor implementing two sequential corrections: a material-specific steady-state slip gain and a discrete linear-advance term parameterized by the identified time constant. For RPP1 at the nominal gain, the print latency interquartile range decreased from 5–20 mm to 2–8 mm without degrading steady-state dimensional accuracy; the combination of nominal gain with active retraction further reduced latency to near-zero. Analysis of covariance (ANCOVA) confirmed that optimal feedforward gains are statistically material-dependent across all three quality metrics (p < 0.05), providing statistical justification for material-specific compensator parameterization. The results establish a practical, hardware-agnostic route to reduce transient deposition defects in pellet-based additive manufacturing, extensible to additional feedstocks.

]]> Transient Characterization and Feedforward Compensation in Fused Granular Fabrication Using Post-Consumer Recycled and Wood-Filled Polypropylenes Stiven Kodra David O. Kazmer Mitchell Mashburn Eric Gohl Patrick Ferrell doi: 10.3390/jmmp10080263 Journal of Manufacturing and Materials Processing 2026-07-23 Journal of Manufacturing and Materials Processing 2026-07-23 10 8 Article 263 10.3390/jmmp10080263 https://www.mdpi.com/2504-4494/10/8/263 JMMP, Vol. 10, Pages 262: Improvement in Surface Integrity and High-Cycle Fatigue of 42CrMo4 Steel Axles and Shafts by Single-Toroidal-Roller Burnishing https://www.mdpi.com/2504-4494/10/8/262 This article presents an optimised deep rolling process, implemented using a single-toroidal-roller burnishing method, to improve the surface integrity and high-cycle fatigue strength of 42CrMo4 steel axles and shafts. A second-order composition plan, regression analyses, and multi-objective optimisation were employed. The solution was based on a non-dominated sorting genetic algorithm (NSGA-II) and Pareto front search approach. The compromise optimal solution yields an average roughness Ra of 0.190 μm, average surface microhardness of 503 HV, and average surface residual axial stress of –855 MPa. Deep rolling conducted using the selected optimal values (a burnishing force of 1000 N and feed rate of 0.11 mm/rev) of the governing factors achieves stable surface integrity characteristics under multiple repetitions of the process. Rotating bending fatigue tests showed that the positive effect of deep rolling begins to manifest itself after 104 cycles, i.e., in the second half of the high-cycle fatigue field and in the mega-cycle region, where the fatigue strength increases from 390 (after turning and polishing) to 440 MPa (after turning and subsequent deep rolling). 2026-07-23 JMMP, Vol. 10, Pages 262: Improvement in Surface Integrity and High-Cycle Fatigue of 42CrMo4 Steel Axles and Shafts by Single-Toroidal-Roller Burnishing

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080262

Authors: Mariana Ichkova Kalin Anastasov

This article presents an optimised deep rolling process, implemented using a single-toroidal-roller burnishing method, to improve the surface integrity and high-cycle fatigue strength of 42CrMo4 steel axles and shafts. A second-order composition plan, regression analyses, and multi-objective optimisation were employed. The solution was based on a non-dominated sorting genetic algorithm (NSGA-II) and Pareto front search approach. The compromise optimal solution yields an average roughness Ra of 0.190 μm, average surface microhardness of 503 HV, and average surface residual axial stress of –855 MPa. Deep rolling conducted using the selected optimal values (a burnishing force of 1000 N and feed rate of 0.11 mm/rev) of the governing factors achieves stable surface integrity characteristics under multiple repetitions of the process. Rotating bending fatigue tests showed that the positive effect of deep rolling begins to manifest itself after 104 cycles, i.e., in the second half of the high-cycle fatigue field and in the mega-cycle region, where the fatigue strength increases from 390 (after turning and polishing) to 440 MPa (after turning and subsequent deep rolling).

]]> Improvement in Surface Integrity and High-Cycle Fatigue of 42CrMo4 Steel Axles and Shafts by Single-Toroidal-Roller Burnishing Mariana Ichkova Kalin Anastasov doi: 10.3390/jmmp10080262 Journal of Manufacturing and Materials Processing 2026-07-23 Journal of Manufacturing and Materials Processing 2026-07-23 10 8 Article 262 10.3390/jmmp10080262 https://www.mdpi.com/2504-4494/10/8/262 JMMP, Vol. 10, Pages 261: A Reliability- and Energy-Aware Decision-Support Framework for Production–Maintenance Scheduling in Parallel CNC Machining Systems https://www.mdpi.com/2504-4494/10/8/261 In parallel CNC machining systems, machine deterioration can simultaneously increase energy-related operating costs, affect delivery performance, and change the timing of preventive maintenance. This study develops a reliability- and energy-aware decision-support framework for production-maintenance scheduling in a two-machine parallel CNC cell. The model integrates priority sequencing, reliability-based machine assignment during decoding, degradation-dependent energy cost, tardiness penalties, and threshold-triggered preventive maintenance in a unified cost-minimization formulation. A normalized reliability index is updated by a short-horizon exponential degradation function, and the energy term is amplified when machines operate in degraded states. Preventive maintenance is triggered when post-job reliability falls below a specified threshold, restoring the machine’s condition for subsequent production or the next planning horizon. The computational study combines application-inspired machining instances, decoder-space full enumeration for small cases, repeated GA/PSO comparisons, a new algorithm-budget sensitivity experiment, and adapted OR-Library weighted-tardiness benchmarks. Across 270 paired budget-sensitivity runs, GA obtained a lower total cost in 265 cases, whereas PSO retained a shorter average runtime in the matched-budget experiments. Across 90 adapted public-benchmark comparisons, GA obtained a lower total cost in 86 cases. These results show that the framework generates feasible schedules and reveals energy–maintenance–tardiness trade-offs. The algorithmic findings are interpreted as a quality–time trade-off under the tested scalarized cost model, not as a claim of universal algorithmic superiority. 2026-07-23 JMMP, Vol. 10, Pages 261: A Reliability- and Energy-Aware Decision-Support Framework for Production–Maintenance Scheduling in Parallel CNC Machining Systems

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080261

Authors: Zhaoyi Zhang Chen-Yang Cheng Chumpol Yuangyai Nagoor Basha Shaik Ranon Jientrakul

In parallel CNC machining systems, machine deterioration can simultaneously increase energy-related operating costs, affect delivery performance, and change the timing of preventive maintenance. This study develops a reliability- and energy-aware decision-support framework for production-maintenance scheduling in a two-machine parallel CNC cell. The model integrates priority sequencing, reliability-based machine assignment during decoding, degradation-dependent energy cost, tardiness penalties, and threshold-triggered preventive maintenance in a unified cost-minimization formulation. A normalized reliability index is updated by a short-horizon exponential degradation function, and the energy term is amplified when machines operate in degraded states. Preventive maintenance is triggered when post-job reliability falls below a specified threshold, restoring the machine’s condition for subsequent production or the next planning horizon. The computational study combines application-inspired machining instances, decoder-space full enumeration for small cases, repeated GA/PSO comparisons, a new algorithm-budget sensitivity experiment, and adapted OR-Library weighted-tardiness benchmarks. Across 270 paired budget-sensitivity runs, GA obtained a lower total cost in 265 cases, whereas PSO retained a shorter average runtime in the matched-budget experiments. Across 90 adapted public-benchmark comparisons, GA obtained a lower total cost in 86 cases. These results show that the framework generates feasible schedules and reveals energy–maintenance–tardiness trade-offs. The algorithmic findings are interpreted as a quality–time trade-off under the tested scalarized cost model, not as a claim of universal algorithmic superiority.

]]> A Reliability- and Energy-Aware Decision-Support Framework for Production–Maintenance Scheduling in Parallel CNC Machining Systems Zhaoyi Zhang Chen-Yang Cheng Chumpol Yuangyai Nagoor Basha Shaik Ranon Jientrakul doi: 10.3390/jmmp10080261 Journal of Manufacturing and Materials Processing 2026-07-23 Journal of Manufacturing and Materials Processing 2026-07-23 10 8 Article 261 10.3390/jmmp10080261 https://www.mdpi.com/2504-4494/10/8/261 JMMP, Vol. 10, Pages 260: A Technological Assessment: Aluminium Alloy Gigacasting vs. Conventional Sheet Metal Forming for Automotive Body-in-White Structures https://www.mdpi.com/2504-4494/10/8/260 Gigacasting is emerging as a disruptive manufacturing route for automotive body-in-white structures, especially for electric vehicles, by enabling large aluminium alloy components to replace assemblies traditionally produced from stamped and joined sheet-metal parts. This paper presents a technological assessment of aluminium gigacasting against conventional multi-material mix sheet-metal manufacturing. The comparison addresses product architecture, structural performance, manufacturability, factory organisation, cost, repairability, supply chain implications, and sustainability. Gigacasting offers benefits in part consolidation, reduced joining operations, shorter process chains, and potentially lower non-material manufacturing costs, making it attractive for high-volume, low-variant EV platforms and greenfield production. However, these advantages are counterbalanced by challenges, including high capital investment, limited die life, defect sensitivity, dimensional distortion, mechanical-property variation, and reduced repairability. Recent benchmark data also indicate that total part cost and production-phase CO2 emissions may remain higher than conventional solutions when aluminium material cost, component mass, and aluminium carbon intensity are considered. Conventional sheet-metal architectures retain advantages in modularity, repairability, quality control, tooling flexibility, and lower-risk implementation in brownfield plants. The analysis concludes that gigacasting should not be regarded as a universal replacement for sheet-metal multi-material Body-in-White (BIW) manufacturing but as a platform-dependent technology whose success requires defect control, low-carbon aluminium supply, process-aware simulation and validation, and high and stable production volumes. 2026-07-23 JMMP, Vol. 10, Pages 260: A Technological Assessment: Aluminium Alloy Gigacasting vs. Conventional Sheet Metal Forming for Automotive Body-in-White Structures

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080260

Authors: Matteo Strano Filippo Caroli Antonino Luongo Davide Maglioli Davide Monaci

Gigacasting is emerging as a disruptive manufacturing route for automotive body-in-white structures, especially for electric vehicles, by enabling large aluminium alloy components to replace assemblies traditionally produced from stamped and joined sheet-metal parts. This paper presents a technological assessment of aluminium gigacasting against conventional multi-material mix sheet-metal manufacturing. The comparison addresses product architecture, structural performance, manufacturability, factory organisation, cost, repairability, supply chain implications, and sustainability. Gigacasting offers benefits in part consolidation, reduced joining operations, shorter process chains, and potentially lower non-material manufacturing costs, making it attractive for high-volume, low-variant EV platforms and greenfield production. However, these advantages are counterbalanced by challenges, including high capital investment, limited die life, defect sensitivity, dimensional distortion, mechanical-property variation, and reduced repairability. Recent benchmark data also indicate that total part cost and production-phase CO2 emissions may remain higher than conventional solutions when aluminium material cost, component mass, and aluminium carbon intensity are considered. Conventional sheet-metal architectures retain advantages in modularity, repairability, quality control, tooling flexibility, and lower-risk implementation in brownfield plants. The analysis concludes that gigacasting should not be regarded as a universal replacement for sheet-metal multi-material Body-in-White (BIW) manufacturing but as a platform-dependent technology whose success requires defect control, low-carbon aluminium supply, process-aware simulation and validation, and high and stable production volumes.

]]> A Technological Assessment: Aluminium Alloy Gigacasting vs. Conventional Sheet Metal Forming for Automotive Body-in-White Structures Matteo Strano Filippo Caroli Antonino Luongo Davide Maglioli Davide Monaci doi: 10.3390/jmmp10080260 Journal of Manufacturing and Materials Processing 2026-07-23 Journal of Manufacturing and Materials Processing 2026-07-23 10 8 Review 260 10.3390/jmmp10080260 https://www.mdpi.com/2504-4494/10/8/260 JMMP, Vol. 10, Pages 259: Mechanical Response Under Compression of Dual-Material PLA/ABS Structures in Additive Manufacturing https://www.mdpi.com/2504-4494/10/8/259 Additive manufacturing, particularly Fused Filament Fabrication (FFF), enables the production of multi-material components with tailored mechanical properties; however, the compressive behavior of dual-material polymer systems remains insufficiently explored. This study investigates the compressive mechanical performance of dual-material PLA/ABS specimens fabricated by FFF, with emphasis on the influence of key process parameters. An experimental design based on the Taguchi method was employed to evaluate the effects of raster angle, raster angle variation, and material volume ratio. Compression tests were conducted in accordance with ASTM standards, and the resulting stress–strain data were analyzed to evaluate the compressive response and deformation characteristics. The results indicate that compressive stress values range from approximately 103 MPa to 138 MPa, with the highest performance obtained for specimens with 60% PLA and 40% ABS. Among the examined parameters, the material composition was identified as the most influential factor, followed by raster variation strategy. These findings demonstrate that dual-material configurations can achieve improved compressive performance through appropriate parameter selection, while also highlighting the significance of interfacial integrity between dissimilar materials. The study provides practical insights into the process–structure–property relationships of dual-material FFF structures, showing how raster strategy and PLA/ABS volume ratio influence compressive response and offering experimentally supported guidance for the fabrication of compression-dominated polymer components. 2026-07-23 JMMP, Vol. 10, Pages 259: Mechanical Response Under Compression of Dual-Material PLA/ABS Structures in Additive Manufacturing

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10080259

Authors: Vasileios D. Sagias Leonidas G. Tsantilas Paraskevi Zacharia Dimitrios G. Papageorgiou Antreas Kantaros Constantinos I. Stergiou

Additive manufacturing, particularly Fused Filament Fabrication (FFF), enables the production of multi-material components with tailored mechanical properties; however, the compressive behavior of dual-material polymer systems remains insufficiently explored. This study investigates the compressive mechanical performance of dual-material PLA/ABS specimens fabricated by FFF, with emphasis on the influence of key process parameters. An experimental design based on the Taguchi method was employed to evaluate the effects of raster angle, raster angle variation, and material volume ratio. Compression tests were conducted in accordance with ASTM standards, and the resulting stress–strain data were analyzed to evaluate the compressive response and deformation characteristics. The results indicate that compressive stress values range from approximately 103 MPa to 138 MPa, with the highest performance obtained for specimens with 60% PLA and 40% ABS. Among the examined parameters, the material composition was identified as the most influential factor, followed by raster variation strategy. These findings demonstrate that dual-material configurations can achieve improved compressive performance through appropriate parameter selection, while also highlighting the significance of interfacial integrity between dissimilar materials. The study provides practical insights into the process–structure–property relationships of dual-material FFF structures, showing how raster strategy and PLA/ABS volume ratio influence compressive response and offering experimentally supported guidance for the fabrication of compression-dominated polymer components.

]]> Mechanical Response Under Compression of Dual-Material PLA/ABS Structures in Additive Manufacturing Vasileios D. Sagias Leonidas G. Tsantilas Paraskevi Zacharia Dimitrios G. Papageorgiou Antreas Kantaros Constantinos I. Stergiou doi: 10.3390/jmmp10080259 Journal of Manufacturing and Materials Processing 2026-07-23 Journal of Manufacturing and Materials Processing 2026-07-23 10 8 Article 259 10.3390/jmmp10080259 https://www.mdpi.com/2504-4494/10/8/259 JMMP, Vol. 10, Pages 258: Development of ANN and ANFIS Models for Prediction of Tool Wear in High-Speed Milling https://www.mdpi.com/2504-4494/10/7/258 In precision machining, tool wear is one of the primary factors affecting machining quality and production efficiency. This study developed intelligent prediction models for tool wear in the high-speed milling (HSM) of AISI 1045 medium-carbon steel by integrating robust process design with backpropagation neural networks (BPNN) and adaptive neuro-fuzzy inference systems (ANFIS). Robust process design was employed to optimize the machining parameters, while the hyperparameters of both BPNN and ANFIS models were systematically optimized to improve prediction performance. Tool wear was measured after a fixed cutting length and used to establish the prediction models. The optimized machining parameters reduced tool wear by 53% compared with the worst experimental condition. The optimized BPNN model achieved a prediction accuracy of 96.68%, whereas the ANFIS model with Gaussian membership functions achieved 100%, demonstrating superior predictive performance. The proposed approach effectively combines robust process design and intelligent prediction models to accurately predict tool wear using a limited experimental dataset, providing an efficient methodology for tool wear prediction and machining parameter optimization in intelligent manufacturing applications. 2026-07-22 JMMP, Vol. 10, Pages 258: Development of ANN and ANFIS Models for Prediction of Tool Wear in High-Speed Milling

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070258

Authors: Wei Tai Huang Yi Cheng Pan

In precision machining, tool wear is one of the primary factors affecting machining quality and production efficiency. This study developed intelligent prediction models for tool wear in the high-speed milling (HSM) of AISI 1045 medium-carbon steel by integrating robust process design with backpropagation neural networks (BPNN) and adaptive neuro-fuzzy inference systems (ANFIS). Robust process design was employed to optimize the machining parameters, while the hyperparameters of both BPNN and ANFIS models were systematically optimized to improve prediction performance. Tool wear was measured after a fixed cutting length and used to establish the prediction models. The optimized machining parameters reduced tool wear by 53% compared with the worst experimental condition. The optimized BPNN model achieved a prediction accuracy of 96.68%, whereas the ANFIS model with Gaussian membership functions achieved 100%, demonstrating superior predictive performance. The proposed approach effectively combines robust process design and intelligent prediction models to accurately predict tool wear using a limited experimental dataset, providing an efficient methodology for tool wear prediction and machining parameter optimization in intelligent manufacturing applications.

]]> Development of ANN and ANFIS Models for Prediction of Tool Wear in High-Speed Milling Wei Tai Huang Yi Cheng Pan doi: 10.3390/jmmp10070258 Journal of Manufacturing and Materials Processing 2026-07-22 Journal of Manufacturing and Materials Processing 2026-07-22 10 7 Article 258 10.3390/jmmp10070258 https://www.mdpi.com/2504-4494/10/7/258 JMMP, Vol. 10, Pages 257: Preparing for the Digital Transformation of a Production Shop Floor https://www.mdpi.com/2504-4494/10/7/257 Small and Midsized Manufacturers (SMM) face challenges as they adopt digital technologies to transform their production environment. A Manufacturing Execution System (MES) requires timely accurate data from shop floor processes to efficiently control production operations. An Industrial Internet of Things (IIoT) platform of sensors provides MES software with operational information through a communications network to enable data-driven decision-making. A midsized manufacturer in southeastern Pennsylvania provides comprehensive thermoformed and injected molded products for diverse markets. Their production equipment includes light and heavy gauge thermoforming, polymer calendaring, and Computer Numerical Control (CNC) part trimming equipment supported by air compressors, vacuum pumps, and water chillers. This project partnered a manufacturer with researchers to deploy engineering and information science students to access, catalog, and characterize shop floor Programmable Logic Controllers (PLC) inputs and outputs. Utilizing this critical PLC data, the expert lead team determined quality-critical parameters, machine counters, and fault codes essential for process optimization. 2026-07-22 JMMP, Vol. 10, Pages 257: Preparing for the Digital Transformation of a Production Shop Floor

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070257

Authors: Terrance Speicher Joanna DeFranco Michael Bartolacci Erin Connelly

Small and Midsized Manufacturers (SMM) face challenges as they adopt digital technologies to transform their production environment. A Manufacturing Execution System (MES) requires timely accurate data from shop floor processes to efficiently control production operations. An Industrial Internet of Things (IIoT) platform of sensors provides MES software with operational information through a communications network to enable data-driven decision-making. A midsized manufacturer in southeastern Pennsylvania provides comprehensive thermoformed and injected molded products for diverse markets. Their production equipment includes light and heavy gauge thermoforming, polymer calendaring, and Computer Numerical Control (CNC) part trimming equipment supported by air compressors, vacuum pumps, and water chillers. This project partnered a manufacturer with researchers to deploy engineering and information science students to access, catalog, and characterize shop floor Programmable Logic Controllers (PLC) inputs and outputs. Utilizing this critical PLC data, the expert lead team determined quality-critical parameters, machine counters, and fault codes essential for process optimization.

]]> Preparing for the Digital Transformation of a Production Shop Floor Terrance Speicher Joanna DeFranco Michael Bartolacci Erin Connelly doi: 10.3390/jmmp10070257 Journal of Manufacturing and Materials Processing 2026-07-22 Journal of Manufacturing and Materials Processing 2026-07-22 10 7 Article 257 10.3390/jmmp10070257 https://www.mdpi.com/2504-4494/10/7/257 JMMP, Vol. 10, Pages 256: Impact of Environmental Hydrogen Pressure on Fracture Toughness and Fracture Behavior of X65 Pipeline Steel Welded Joints https://www.mdpi.com/2504-4494/10/7/256 Hydrogen embrittlement (HE) damages the fracture toughness, often promoting brittle fracture even at low stress levels. Since welded joints are sensitive to this kind of damage, there is a very high risk of failure. For this reason, this study systematically evaluates the fracture toughness and fracture behavior of X65 pipeline steel welded joints under a gaseous hydrogen environment. The crack tip opening displacement (CTOD) test and electron microscopy technology were adopted to carry out fracture toughness evaluation and microstructure analysis on the weld metal (WM) and heat-affected zone (HAZ) under hydrogen pressure conditions of 1.0 MPa, as well as 7.2 MPa. The results underscore that at the higher hydrogen pressure (7.2 MPa), the CTOD value decreased compared with that at 1.0 MPa; the reduction amplitudes of the CTOD values of the WM and HAZ were 79% and 84%, respectively. When the hydrogen pressure was 1.0 MPa, the WM and HAZ presented microvoid coalescence (MVC) fracture characteristics, the crack propagation path was tortuous, the plastic deformation at the crack tip was significant, and dislocations proliferated massively, leading to high fracture toughness. At 7.2 MPa, the fracture mechanism was into brittle fracture, the crack propagated along an almost straight path, plastic deformation and dislocation proliferation at the crack tip were significantly inhibited, and the fracture toughness decreased sharply. 2026-07-22 JMMP, Vol. 10, Pages 256: Impact of Environmental Hydrogen Pressure on Fracture Toughness and Fracture Behavior of X65 Pipeline Steel Welded Joints

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070256

Authors: Xue Yin Xue Wang Yuezhang Ju Zhaoqing Yang Xinjie Di

Hydrogen embrittlement (HE) damages the fracture toughness, often promoting brittle fracture even at low stress levels. Since welded joints are sensitive to this kind of damage, there is a very high risk of failure. For this reason, this study systematically evaluates the fracture toughness and fracture behavior of X65 pipeline steel welded joints under a gaseous hydrogen environment. The crack tip opening displacement (CTOD) test and electron microscopy technology were adopted to carry out fracture toughness evaluation and microstructure analysis on the weld metal (WM) and heat-affected zone (HAZ) under hydrogen pressure conditions of 1.0 MPa, as well as 7.2 MPa. The results underscore that at the higher hydrogen pressure (7.2 MPa), the CTOD value decreased compared with that at 1.0 MPa; the reduction amplitudes of the CTOD values of the WM and HAZ were 79% and 84%, respectively. When the hydrogen pressure was 1.0 MPa, the WM and HAZ presented microvoid coalescence (MVC) fracture characteristics, the crack propagation path was tortuous, the plastic deformation at the crack tip was significant, and dislocations proliferated massively, leading to high fracture toughness. At 7.2 MPa, the fracture mechanism was into brittle fracture, the crack propagated along an almost straight path, plastic deformation and dislocation proliferation at the crack tip were significantly inhibited, and the fracture toughness decreased sharply.

]]> Impact of Environmental Hydrogen Pressure on Fracture Toughness and Fracture Behavior of X65 Pipeline Steel Welded Joints Xue Yin Xue Wang Yuezhang Ju Zhaoqing Yang Xinjie Di doi: 10.3390/jmmp10070256 Journal of Manufacturing and Materials Processing 2026-07-22 Journal of Manufacturing and Materials Processing 2026-07-22 10 7 Article 256 10.3390/jmmp10070256 https://www.mdpi.com/2504-4494/10/7/256 JMMP, Vol. 10, Pages 255: Laser Remelting-Induced Microstructure Refinement and Strengthening of (TaWZrHf)95Y5 Refractory High-Entropy Alloy https://www.mdpi.com/2504-4494/10/7/255 A novel (TaWZrHf)95Y5 refractory high-entropy alloy (RHEA) matrix was fabricated via vacuum hot pressing (VHP) sintering and subsequently modified through laser remelting (LR) surface treatment. Thermodynamic phase diagram calculations predicted the alloy’s dual-phase BCC structure, and the effects of LR on phase composition, microstructure, and mechanical properties were systematically investigated. LR induced a significant phase transition, promoting rapid solidification and substantial grain refinement. The surface hardness increased to 848 HV0.2, approximately 1.5 times higher than that of the matrix, while the compressive strength reached 1635 MPa, surpassing the matrix by 200 MPa without compromising ductility. Importantly, the LR process effectively mitigated rare-earth (yttrium) segregation and loss, a common challenge in conventional arc melting of refractory HEAs, thereby enhancing solid solution strengthening and phase stability. This work pioneers the application of laser surface engineering to VHP-sintered refractory HEAs, bridging critical gaps in fabrication, microstructural optimization, and performance enhancement, and offering valuable insights for the future design of high-performance multi-principal element alloy development. 2026-07-21 JMMP, Vol. 10, Pages 255: Laser Remelting-Induced Microstructure Refinement and Strengthening of (TaWZrHf)95Y5 Refractory High-Entropy Alloy

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070255

Authors: Chuanbing Huang Junnan Jin Yonghui Sun Hao Lan Weigang Zhang

A novel (TaWZrHf)95Y5 refractory high-entropy alloy (RHEA) matrix was fabricated via vacuum hot pressing (VHP) sintering and subsequently modified through laser remelting (LR) surface treatment. Thermodynamic phase diagram calculations predicted the alloy’s dual-phase BCC structure, and the effects of LR on phase composition, microstructure, and mechanical properties were systematically investigated. LR induced a significant phase transition, promoting rapid solidification and substantial grain refinement. The surface hardness increased to 848 HV0.2, approximately 1.5 times higher than that of the matrix, while the compressive strength reached 1635 MPa, surpassing the matrix by 200 MPa without compromising ductility. Importantly, the LR process effectively mitigated rare-earth (yttrium) segregation and loss, a common challenge in conventional arc melting of refractory HEAs, thereby enhancing solid solution strengthening and phase stability. This work pioneers the application of laser surface engineering to VHP-sintered refractory HEAs, bridging critical gaps in fabrication, microstructural optimization, and performance enhancement, and offering valuable insights for the future design of high-performance multi-principal element alloy development.

]]> Laser Remelting-Induced Microstructure Refinement and Strengthening of (TaWZrHf)95Y5 Refractory High-Entropy Alloy Chuanbing Huang Junnan Jin Yonghui Sun Hao Lan Weigang Zhang doi: 10.3390/jmmp10070255 Journal of Manufacturing and Materials Processing 2026-07-21 Journal of Manufacturing and Materials Processing 2026-07-21 10 7 Article 255 10.3390/jmmp10070255 https://www.mdpi.com/2504-4494/10/7/255 JMMP, Vol. 10, Pages 254: Machine Learning-Guided Optimization of Defects in In-Situ Alloyed Additively Manufactured Parts https://www.mdpi.com/2504-4494/10/7/254 In-situ alloying during laser powder bed fusion (LPBF) offers great compositional flexibility but is prone to process-induced defects. To address this problem, we developed a machine learning framework to predict and minimize major defects such as porosity (inclusive of lack of fusion, gas pores, and keyhole-induced porosity) and unmelted Nb particles (partially and completely unmelted particles) in LPBF-fabricated in-situ alloyed Ti–45Nb alloy. For this purpose, two independent least-squares boosting (LSBoost) ensemble regressors were trained using five process parameters (part shape, laser power, scan speed, hatch spacing, and scan rotation), along with their polynomial and interaction terms, to capture nonlinear relationships. Under a restricted 4-fold cross-validation, these models achieved pooled out-of-fold R2 values of 0.672 for porosity and 0.702 for unmelted Nb, despite being trained on a small dataset. The grouped permutation importance analysis revealed that porosity is primarily governed by hatch spacing and laser power, whereas unmelted Nb particles are primarily governed by laser power and scan speed. The models were implemented in two graphical interfaces: a forward predictor for real-time defect estimation and an inverse optimizer for identifying low-defect parameter sets. Together, they establish a unified, data-driven approach for defect-aware process detection, prediction, and optimization in in-situ alloyed systems, offering a pathway towards reproducible, low-defect additive manufacturing. 2026-07-21 JMMP, Vol. 10, Pages 254: Machine Learning-Guided Optimization of Defects in In-Situ Alloyed Additively Manufactured Parts

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070254

Authors: Shaaf Shelesh Nezhad Sravya Tekumalla

In-situ alloying during laser powder bed fusion (LPBF) offers great compositional flexibility but is prone to process-induced defects. To address this problem, we developed a machine learning framework to predict and minimize major defects such as porosity (inclusive of lack of fusion, gas pores, and keyhole-induced porosity) and unmelted Nb particles (partially and completely unmelted particles) in LPBF-fabricated in-situ alloyed Ti–45Nb alloy. For this purpose, two independent least-squares boosting (LSBoost) ensemble regressors were trained using five process parameters (part shape, laser power, scan speed, hatch spacing, and scan rotation), along with their polynomial and interaction terms, to capture nonlinear relationships. Under a restricted 4-fold cross-validation, these models achieved pooled out-of-fold R2 values of 0.672 for porosity and 0.702 for unmelted Nb, despite being trained on a small dataset. The grouped permutation importance analysis revealed that porosity is primarily governed by hatch spacing and laser power, whereas unmelted Nb particles are primarily governed by laser power and scan speed. The models were implemented in two graphical interfaces: a forward predictor for real-time defect estimation and an inverse optimizer for identifying low-defect parameter sets. Together, they establish a unified, data-driven approach for defect-aware process detection, prediction, and optimization in in-situ alloyed systems, offering a pathway towards reproducible, low-defect additive manufacturing.

]]> Machine Learning-Guided Optimization of Defects in In-Situ Alloyed Additively Manufactured Parts Shaaf Shelesh Nezhad Sravya Tekumalla doi: 10.3390/jmmp10070254 Journal of Manufacturing and Materials Processing 2026-07-21 Journal of Manufacturing and Materials Processing 2026-07-21 10 7 Article 254 10.3390/jmmp10070254 https://www.mdpi.com/2504-4494/10/7/254 JMMP, Vol. 10, Pages 253: Particle Size Refinement and Kinetic Modeling of Hercynite Powders Under Wet Mechanical Milling https://www.mdpi.com/2504-4494/10/7/253 The particle size refinement of hercynite (FeAl2O4) powders during wet high-energy mechanical milling was investigated through an integrated experimental and kinetic modeling approach. Hercynite powders were milled for different durations, and their microstructural, chemical, and particle size evolution was characterized using scanning electron microscopy, X-ray diffraction, semi-quantitative X-ray fluorescence analysis, and SEM–ImageJ-based particle size reconstruction. Particle size distributions were reconstructed from large particle populations, and the characteristic descriptors D10, D50, and D90 were determined from empirical cumulative distributions. The results revealed a pronounced reduction in median particle size from approximately 83.1 μm in the as-received powder to 0.422 μm after 8 h of milling. X-ray diffraction analysis showed progressive peak broadening and intensity reduction with increasing milling time, suggesting milling-induced structural disorder and possible crystallite refinement and/or lattice strain accumulation, while no additional crystalline phases associated with milling-induced decomposition were detected within the detection limit of XRD. Semi-quantitative chemical analysis indicated limited metallic transfer from the stainless-steel milling media under the applied wet milling conditions. The evolution of D50 with milling time exhibited a non-linear behavior characterized by rapid particle fragmentation at early stages, followed by a gradual transition toward a refinement-limited regime. This behavior was described using a first-order kinetic model with saturation behavior, yielding an asymptotic particle size of 0.443 μm and an effective milling rate constant of 1.539 h−1. Overall, the proposed kinetic framework provides a descriptive and condition-specific quantitative basis for interpreting the competing fracture and agglomeration mechanisms governing particle size evolution during wet mechanical milling of refractory spinel powders. 2026-07-21 JMMP, Vol. 10, Pages 253: Particle Size Refinement and Kinetic Modeling of Hercynite Powders Under Wet Mechanical Milling

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070253

Authors: Leonel Díaz-Tato Luis Angel Iturralde Carrera Edgar Omar García-Sánchez Yoisdel Castillo Alvarez Ismael Flores-Vivian Juan Jacobo Ruiz-Valdés Juvenal Rodríguez-Reséndiz Edén Amaral Rodríguez-Castellanos

The particle size refinement of hercynite (FeAl2O4) powders during wet high-energy mechanical milling was investigated through an integrated experimental and kinetic modeling approach. Hercynite powders were milled for different durations, and their microstructural, chemical, and particle size evolution was characterized using scanning electron microscopy, X-ray diffraction, semi-quantitative X-ray fluorescence analysis, and SEM–ImageJ-based particle size reconstruction. Particle size distributions were reconstructed from large particle populations, and the characteristic descriptors D10, D50, and D90 were determined from empirical cumulative distributions. The results revealed a pronounced reduction in median particle size from approximately 83.1 μm in the as-received powder to 0.422 μm after 8 h of milling. X-ray diffraction analysis showed progressive peak broadening and intensity reduction with increasing milling time, suggesting milling-induced structural disorder and possible crystallite refinement and/or lattice strain accumulation, while no additional crystalline phases associated with milling-induced decomposition were detected within the detection limit of XRD. Semi-quantitative chemical analysis indicated limited metallic transfer from the stainless-steel milling media under the applied wet milling conditions. The evolution of D50 with milling time exhibited a non-linear behavior characterized by rapid particle fragmentation at early stages, followed by a gradual transition toward a refinement-limited regime. This behavior was described using a first-order kinetic model with saturation behavior, yielding an asymptotic particle size of 0.443 μm and an effective milling rate constant of 1.539 h−1. Overall, the proposed kinetic framework provides a descriptive and condition-specific quantitative basis for interpreting the competing fracture and agglomeration mechanisms governing particle size evolution during wet mechanical milling of refractory spinel powders.

]]> Particle Size Refinement and Kinetic Modeling of Hercynite Powders Under Wet Mechanical Milling Leonel Díaz-Tato Luis Angel Iturralde Carrera Edgar Omar García-Sánchez Yoisdel Castillo Alvarez Ismael Flores-Vivian Juan Jacobo Ruiz-Valdés Juvenal Rodríguez-Reséndiz Edén Amaral Rodríguez-Castellanos doi: 10.3390/jmmp10070253 Journal of Manufacturing and Materials Processing 2026-07-21 Journal of Manufacturing and Materials Processing 2026-07-21 10 7 Article 253 10.3390/jmmp10070253 https://www.mdpi.com/2504-4494/10/7/253 JMMP, Vol. 10, Pages 252: Effect of Active Air-Cooling Configuration During Interlayer Friction Stir Processing on Grain Morphology and Within-Wall Homogeneity in UAMFSP-Fabricated Aluminum 4043 Walls: A Single-Replicate Exploratory Study https://www.mdpi.com/2504-4494/10/7/252 The Unified Additive-Deformation Manufacturing Process (UAMFSP) integrates MIG-based Wire Arc Additive Manufacturing (WAAM) with interlayer Friction Stir Processing (FSP) on a single CNC platform, applying severe plastic deformation to each deposited layer. The novelty of this work is the first controlled comparison, to the authors’ knowledge, of the spatial position of forced-air cooling applied concurrently with the FSP traverse in such an integrated platform: cooling was directed at the top bead surface (TC), at the bottom substrate (BC), or at both surfaces simultaneously (DC), with a MIG-only wall serving as the baseline. Single-layer, four-bead ER4043 aluminum walls were deposited on AA6061 substrates, and optical micrographs from three within-bead locations per condition were quantified with ImageJ, yielding 2038 to 2723 grains per condition. A lumped-parameter thermal model calibrated to infrared thermography ranked the comparative cooling rates as NC < TC < BC < DC. The principal finding is grain homogenization: every FSP condition reduced the grain area scatter by 55 to 71 percent relative to MIG-only, eliminating the coarse-grain tail of the as-deposited distribution regardless of cooling position. Mean equivalent diameters of all four conditions lie within 0.5 µm of one another, at the resolution limit of the optical measurement, so the mean-size ordering (DC finest, 2.76 µm) is reported as a ranking rather than as net refinement. Vickers microhardness on the MIG-only and uncooled FSP walls revealed a 27 HV within-wall gradient (86 ± 7 HV at the stir-zone center versus 59 ± 2 HV at the bead edge), which motivates bilateral cooling for thermal-field homogenization. Because the design is single-replicate, between-condition differences are presented as hypotheses for replicate study with EBSD and spatially resolved hardness mapping. 2026-07-20 JMMP, Vol. 10, Pages 252: Effect of Active Air-Cooling Configuration During Interlayer Friction Stir Processing on Grain Morphology and Within-Wall Homogeneity in UAMFSP-Fabricated Aluminum 4043 Walls: A Single-Replicate Exploratory Study

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070252

Authors: Ahmed Nabil Elalem Husam Alrehaili Xin Wu

The Unified Additive-Deformation Manufacturing Process (UAMFSP) integrates MIG-based Wire Arc Additive Manufacturing (WAAM) with interlayer Friction Stir Processing (FSP) on a single CNC platform, applying severe plastic deformation to each deposited layer. The novelty of this work is the first controlled comparison, to the authors’ knowledge, of the spatial position of forced-air cooling applied concurrently with the FSP traverse in such an integrated platform: cooling was directed at the top bead surface (TC), at the bottom substrate (BC), or at both surfaces simultaneously (DC), with a MIG-only wall serving as the baseline. Single-layer, four-bead ER4043 aluminum walls were deposited on AA6061 substrates, and optical micrographs from three within-bead locations per condition were quantified with ImageJ, yielding 2038 to 2723 grains per condition. A lumped-parameter thermal model calibrated to infrared thermography ranked the comparative cooling rates as NC < TC < BC < DC. The principal finding is grain homogenization: every FSP condition reduced the grain area scatter by 55 to 71 percent relative to MIG-only, eliminating the coarse-grain tail of the as-deposited distribution regardless of cooling position. Mean equivalent diameters of all four conditions lie within 0.5 µm of one another, at the resolution limit of the optical measurement, so the mean-size ordering (DC finest, 2.76 µm) is reported as a ranking rather than as net refinement. Vickers microhardness on the MIG-only and uncooled FSP walls revealed a 27 HV within-wall gradient (86 ± 7 HV at the stir-zone center versus 59 ± 2 HV at the bead edge), which motivates bilateral cooling for thermal-field homogenization. Because the design is single-replicate, between-condition differences are presented as hypotheses for replicate study with EBSD and spatially resolved hardness mapping.

]]> Effect of Active Air-Cooling Configuration During Interlayer Friction Stir Processing on Grain Morphology and Within-Wall Homogeneity in UAMFSP-Fabricated Aluminum 4043 Walls: A Single-Replicate Exploratory Study Ahmed Nabil Elalem Husam Alrehaili Xin Wu doi: 10.3390/jmmp10070252 Journal of Manufacturing and Materials Processing 2026-07-20 Journal of Manufacturing and Materials Processing 2026-07-20 10 7 Article 252 10.3390/jmmp10070252 https://www.mdpi.com/2504-4494/10/7/252 JMMP, Vol. 10, Pages 251: Synthesis of Mo–Ti–Ta–Cr Alloy Powders by Calciothermic Reduction https://www.mdpi.com/2504-4494/10/7/251 In this work, the synthesis of Mo–Ti–Ta–Cr alloy powders via the calciothermic reduction (CTR) of MoO3, TiO2, Ta2O5, and Cr2O3 was investigated. The synthesis process was supported by thermodynamic calculations and TG–DSC thermal analysis. XRD analysis of the synthesized powder confirmed the formation of Mo-based BCC solid solutions. Microstructural studies have documented the formation of submicron-sized powder particles. A mechanism for Mo-based alloy formation has been proposed. 2026-07-19 JMMP, Vol. 10, Pages 251: Synthesis of Mo–Ti–Ta–Cr Alloy Powders by Calciothermic Reduction

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070251

Authors: Mariia Teslia Serhii Teslia Ievgen Solodkyi

In this work, the synthesis of Mo–Ti–Ta–Cr alloy powders via the calciothermic reduction (CTR) of MoO3, TiO2, Ta2O5, and Cr2O3 was investigated. The synthesis process was supported by thermodynamic calculations and TG–DSC thermal analysis. XRD analysis of the synthesized powder confirmed the formation of Mo-based BCC solid solutions. Microstructural studies have documented the formation of submicron-sized powder particles. A mechanism for Mo-based alloy formation has been proposed.

]]> Synthesis of Mo–Ti–Ta–Cr Alloy Powders by Calciothermic Reduction Mariia Teslia Serhii Teslia Ievgen Solodkyi doi: 10.3390/jmmp10070251 Journal of Manufacturing and Materials Processing 2026-07-19 Journal of Manufacturing and Materials Processing 2026-07-19 10 7 Article 251 10.3390/jmmp10070251 https://www.mdpi.com/2504-4494/10/7/251 JMMP, Vol. 10, Pages 250: Prioritization of Process Improvement Measures in a Forging Process Using an IPF-AHP-Based SREM Framework https://www.mdpi.com/2504-4494/10/7/250 Forging represents a very important process in the metal processing industry, for which risk analysis and continuous improvement activities are required in order to satisfy customer requirements regarding product quality and mechanical properties. In practice, Process Failure Mode and Effects Analysis (PFMEA) is used for risk identification and assessment. However, since this analysis provides only recommended process improvement measures as an output, without prioritizing them according to technical, economic, and operational aspects, this study develops a Multi-Criteria Decision-Making (MCDM) approach based on the integration of the Analytic Hierarchy Process (AHP) and the Square-Root-Based Evaluation Method (SREM), extended through the application of Interval-Valued Pythagorean Fuzzy Numbers (IVPFNs) to model uncertainty in the assessments of the expert team. In this way, a decision-making framework was developed that enables the prioritization of process improvement measures identified through PFMEA in an exact and mathematically based manner. The proposed approach was tested through a case study conducted in a company primarily engaged in the production of forgings as a supplier to various industrial sectors. A total of six process improvement measures were considered and evaluated with respect to seven technical, economic, and operational criteria. The results of the study clearly demonstrated that the additional die-leading measure ranked first and represented the most stable solution, maintaining its leading position regardless of the changes introduced through the sensitivity analysis. 2026-07-19 JMMP, Vol. 10, Pages 250: Prioritization of Process Improvement Measures in a Forging Process Using an IPF-AHP-Based SREM Framework

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070250

Authors: Nikola Kastratović Dušan Arsić Nikola Komatina Marko Delić Dragan Marinković

Forging represents a very important process in the metal processing industry, for which risk analysis and continuous improvement activities are required in order to satisfy customer requirements regarding product quality and mechanical properties. In practice, Process Failure Mode and Effects Analysis (PFMEA) is used for risk identification and assessment. However, since this analysis provides only recommended process improvement measures as an output, without prioritizing them according to technical, economic, and operational aspects, this study develops a Multi-Criteria Decision-Making (MCDM) approach based on the integration of the Analytic Hierarchy Process (AHP) and the Square-Root-Based Evaluation Method (SREM), extended through the application of Interval-Valued Pythagorean Fuzzy Numbers (IVPFNs) to model uncertainty in the assessments of the expert team. In this way, a decision-making framework was developed that enables the prioritization of process improvement measures identified through PFMEA in an exact and mathematically based manner. The proposed approach was tested through a case study conducted in a company primarily engaged in the production of forgings as a supplier to various industrial sectors. A total of six process improvement measures were considered and evaluated with respect to seven technical, economic, and operational criteria. The results of the study clearly demonstrated that the additional die-leading measure ranked first and represented the most stable solution, maintaining its leading position regardless of the changes introduced through the sensitivity analysis.

]]> Prioritization of Process Improvement Measures in a Forging Process Using an IPF-AHP-Based SREM Framework Nikola Kastratović Dušan Arsić Nikola Komatina Marko Delić Dragan Marinković doi: 10.3390/jmmp10070250 Journal of Manufacturing and Materials Processing 2026-07-19 Journal of Manufacturing and Materials Processing 2026-07-19 10 7 Article 250 10.3390/jmmp10070250 https://www.mdpi.com/2504-4494/10/7/250 JMMP, Vol. 10, Pages 249: 3D-Printed PLA Gyroid Filter Supports: Manufacturing, Mechanical Response and Hydrochar Deposition Screening https://www.mdpi.com/2504-4494/10/7/249 This study investigates the design, fabrication, and manufacturing/mechanical characterization of 3D-printed polylactic acid (PLA) cylindrical filter supports developed as substrates for subsequent hydrochar functionalization. Filters with an outer diameter of 30 mm, a height of 20 mm, and a wall thickness of 3 mm were manufactured by material extrusion additive manufacturing and internally filled with gyroid architectures generated in Bambu Studio at three density levels, namely 10%, 15%, and 20%. The printed filters were first evaluated in terms of weight and compressive response. The main focus of the work was the manufacturing consistency and mechanical response of the gyroid supports, while hydrochar deposition was considered as an initial functionalization screening step. The results showed that increasing gyroid density led to higher maximum compressive stress, while mass-normalized analysis revealed a trade-off between absolute mechanical resistance and material efficiency. Surface-treatment screening trials were then carried out on flat PLA specimens to evaluate whether algae-derived hydrochar could be retained on PLA after alkaline activation. Visual and SEM observations showed partial and heterogeneous hydrochar-related surface coverage, with localized agglomerates and partial masking of the original printing lines, but without the formation of a homogeneous coating. EDX analysis of selected agglomerates revealed C and O together with Na, Cl, K, and Ca, supporting the presence of hydrochar-related/mineral-containing deposits on the treated PLA surface, although K may also be associated with residual species from the KOH activation step. FTIR analysis did not reveal clear hydrochar-related spectral features, indicating that FTIR alone was not sufficient to demonstrate effective homogeneous surface functionalization and supporting the interpretation of heterogeneous surface retention. Overall, the study provides a first manufacturing-oriented basis for PLA gyroid filter supports intended for hydrochar deposition and highlights the need for improved surface activation strategies before subsequent functional validation. 2026-07-18 JMMP, Vol. 10, Pages 249: 3D-Printed PLA Gyroid Filter Supports: Manufacturing, Mechanical Response and Hydrochar Deposition Screening

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070249

Authors: Mohamed Chairi Viviana Bressi Mariasofia Parisi Tiziana Cappello Claudia Espro Guido Di Bella

This study investigates the design, fabrication, and manufacturing/mechanical characterization of 3D-printed polylactic acid (PLA) cylindrical filter supports developed as substrates for subsequent hydrochar functionalization. Filters with an outer diameter of 30 mm, a height of 20 mm, and a wall thickness of 3 mm were manufactured by material extrusion additive manufacturing and internally filled with gyroid architectures generated in Bambu Studio at three density levels, namely 10%, 15%, and 20%. The printed filters were first evaluated in terms of weight and compressive response. The main focus of the work was the manufacturing consistency and mechanical response of the gyroid supports, while hydrochar deposition was considered as an initial functionalization screening step. The results showed that increasing gyroid density led to higher maximum compressive stress, while mass-normalized analysis revealed a trade-off between absolute mechanical resistance and material efficiency. Surface-treatment screening trials were then carried out on flat PLA specimens to evaluate whether algae-derived hydrochar could be retained on PLA after alkaline activation. Visual and SEM observations showed partial and heterogeneous hydrochar-related surface coverage, with localized agglomerates and partial masking of the original printing lines, but without the formation of a homogeneous coating. EDX analysis of selected agglomerates revealed C and O together with Na, Cl, K, and Ca, supporting the presence of hydrochar-related/mineral-containing deposits on the treated PLA surface, although K may also be associated with residual species from the KOH activation step. FTIR analysis did not reveal clear hydrochar-related spectral features, indicating that FTIR alone was not sufficient to demonstrate effective homogeneous surface functionalization and supporting the interpretation of heterogeneous surface retention. Overall, the study provides a first manufacturing-oriented basis for PLA gyroid filter supports intended for hydrochar deposition and highlights the need for improved surface activation strategies before subsequent functional validation.

]]> 3D-Printed PLA Gyroid Filter Supports: Manufacturing, Mechanical Response and Hydrochar Deposition Screening Mohamed Chairi Viviana Bressi Mariasofia Parisi Tiziana Cappello Claudia Espro Guido Di Bella doi: 10.3390/jmmp10070249 Journal of Manufacturing and Materials Processing 2026-07-18 Journal of Manufacturing and Materials Processing 2026-07-18 10 7 Article 249 10.3390/jmmp10070249 https://www.mdpi.com/2504-4494/10/7/249 JMMP, Vol. 10, Pages 248: Analysis of the Fracture Toughness of ERCuAl A2 Cladding on API X70 Using the Instrumented Charpy Impact Test https://www.mdpi.com/2504-4494/10/7/248 The degradation of steel used in the oil industry has become a serious problem due to the high costs associated with material loss from corrosion. Applying thin layers of corrosion-resistant material promises to be a viable alternative for extending the service life of pipelines. ERCuAl-A2 electrode claddings were applied to API X70 carbon steel using the MIG brazing process with direct current (DC) and pulsed current (P). The cladding was applied under three conditions: base material (BM) at room temperature, BM preheated to 120 °C, and Ni-buttered BM. Microhardness profiles and Charpy impact tests were performed on the MB and all cladding conditions. The API X70 carbon steel showed a microhardness value of 186.95 ± 11.17 Vickers, while the microhardness profiles of the ERCuAl A2 cladding showed values that differed in the intermetallic zone generated by the welding process. Likewise, the impact behavior of the base material and the applied claddings was ductile, except for conditions C2PF and C3PF, which showed a brittle–ductile behavior. The highest values of absorbed energy obtained from the tests were found in the conditions applied with DC, with values of approximately 50 MJm-3, due to the transfer mode of application of the cladding and/or the position in which the notch was made. 2026-07-15 JMMP, Vol. 10, Pages 248: Analysis of the Fracture Toughness of ERCuAl A2 Cladding on API X70 Using the Instrumented Charpy Impact Test

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070248

Authors: Martín Aguirre-Pulido Francisco Fernando Curiel-López José Jaime Taha-Tijerina Jorge Alejandro Verduzco-Martínez Víctor Hugo López-Morelos Heriberto Granados-Becerra Ariosto Medina-Flores

The degradation of steel used in the oil industry has become a serious problem due to the high costs associated with material loss from corrosion. Applying thin layers of corrosion-resistant material promises to be a viable alternative for extending the service life of pipelines. ERCuAl-A2 electrode claddings were applied to API X70 carbon steel using the MIG brazing process with direct current (DC) and pulsed current (P). The cladding was applied under three conditions: base material (BM) at room temperature, BM preheated to 120 °C, and Ni-buttered BM. Microhardness profiles and Charpy impact tests were performed on the MB and all cladding conditions. The API X70 carbon steel showed a microhardness value of 186.95 ± 11.17 Vickers, while the microhardness profiles of the ERCuAl A2 cladding showed values that differed in the intermetallic zone generated by the welding process. Likewise, the impact behavior of the base material and the applied claddings was ductile, except for conditions C2PF and C3PF, which showed a brittle–ductile behavior. The highest values of absorbed energy obtained from the tests were found in the conditions applied with DC, with values of approximately 50 MJm-3, due to the transfer mode of application of the cladding and/or the position in which the notch was made.

]]> Analysis of the Fracture Toughness of ERCuAl A2 Cladding on API X70 Using the Instrumented Charpy Impact Test Martín Aguirre-Pulido Francisco Fernando Curiel-López José Jaime Taha-Tijerina Jorge Alejandro Verduzco-Martínez Víctor Hugo López-Morelos Heriberto Granados-Becerra Ariosto Medina-Flores doi: 10.3390/jmmp10070248 Journal of Manufacturing and Materials Processing 2026-07-15 Journal of Manufacturing and Materials Processing 2026-07-15 10 7 Article 248 10.3390/jmmp10070248 https://www.mdpi.com/2504-4494/10/7/248 JMMP, Vol. 10, Pages 247: An Experimental Study on SiC Nanofluid-Assisted MQL in Hard Milling of AISI D2 Tool Steel https://www.mdpi.com/2504-4494/10/7/247 The new technological solutions supporting hard machining processes are becoming an up-to-date research area. The enhancement of cooling lubrication efficiency in the cutting zone plays a crucial role in improving cutting performance. This paper investigates the effectiveness of Minimum Quantity Lubrication (MQL) using SiC nanoparticle-enhanced oil in the hard milling process of AISI D2 tool steel. The results are compared with dry and pure MQL modes based on criteria including cutting force components, surface roughness, tool wear, and tool life. The research results show that compared to dry and pure MQL, the SiC nanofluid MQL environment provides the best performance with reductions in feed force Fx (22.3–23.8%), thrust force Fy (20.5–55.3%), tangential force Fz (26.5–34%), surface roughness (37–62.3%), tool wear (46.1–73.3%), and increased tool life (80–200%). These findings demonstrate that the lubrication and cooling efficiency of the base oil is improved with the addition of SiC nanoparticles. The deep penetration of oil droplets into the cutting zone and the formation of the oil film significantly contributed to reducing friction and cutting heat. SiC nanoparticles not only improved the lubricating and cooling capabilities of the base cutting oil but also created secondary mechanisms within the cutting zone. Furthermore, monitoring cutting forces and surface roughness can be suggested as supplementary criteria for evaluating tool wear and tool life. This research will provide important technological guidance and a theoretical basis for the improvement of hard milling and application of the SiC nanofluid MQL technique. 2026-07-14 JMMP, Vol. 10, Pages 247: An Experimental Study on SiC Nanofluid-Assisted MQL in Hard Milling of AISI D2 Tool Steel

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070247

Authors: Ngo Minh Tuan Tran Minh Duc Nguyen The Doan Tran Ngoc Diep Vu Nhu Nguyet Tran The Long

The new technological solutions supporting hard machining processes are becoming an up-to-date research area. The enhancement of cooling lubrication efficiency in the cutting zone plays a crucial role in improving cutting performance. This paper investigates the effectiveness of Minimum Quantity Lubrication (MQL) using SiC nanoparticle-enhanced oil in the hard milling process of AISI D2 tool steel. The results are compared with dry and pure MQL modes based on criteria including cutting force components, surface roughness, tool wear, and tool life. The research results show that compared to dry and pure MQL, the SiC nanofluid MQL environment provides the best performance with reductions in feed force Fx (22.3–23.8%), thrust force Fy (20.5–55.3%), tangential force Fz (26.5–34%), surface roughness (37–62.3%), tool wear (46.1–73.3%), and increased tool life (80–200%). These findings demonstrate that the lubrication and cooling efficiency of the base oil is improved with the addition of SiC nanoparticles. The deep penetration of oil droplets into the cutting zone and the formation of the oil film significantly contributed to reducing friction and cutting heat. SiC nanoparticles not only improved the lubricating and cooling capabilities of the base cutting oil but also created secondary mechanisms within the cutting zone. Furthermore, monitoring cutting forces and surface roughness can be suggested as supplementary criteria for evaluating tool wear and tool life. This research will provide important technological guidance and a theoretical basis for the improvement of hard milling and application of the SiC nanofluid MQL technique.

]]> An Experimental Study on SiC Nanofluid-Assisted MQL in Hard Milling of AISI D2 Tool Steel Ngo Minh Tuan Tran Minh Duc Nguyen The Doan Tran Ngoc Diep Vu Nhu Nguyet Tran The Long doi: 10.3390/jmmp10070247 Journal of Manufacturing and Materials Processing 2026-07-14 Journal of Manufacturing and Materials Processing 2026-07-14 10 7 Article 247 10.3390/jmmp10070247 https://www.mdpi.com/2504-4494/10/7/247 JMMP, Vol. 10, Pages 246: The Influence of Mixing Modes on Structure Formation and Mechanical Properties of Ti-Al-Fe-O-C Powder Materials During Vacuum Sintering https://www.mdpi.com/2504-4494/10/7/246 One of the possible ways to increase the functional properties of titanium-based composites is the use of additional components in the form of solid inclusions of oxides, carbides, etc. The key task in this case is to achieve a uniform distribution of such inclusions in the structure of the material. This study demonstrates that this problem can be more effectively solved at the stage of preparing the powder mixture from which a titanium matrix composite is subsequently obtained. The paper presents the results of a study of the structure and mechanical properties of sintered powder materials of the Ti-Al-Fe-O-C system using two procedures for mixing the initial components. In the first case, traditional mixing of titanium, aluminum, soot and iron oxide Fe2O3 powders was used, and in the second case, a two-stage procedure was used with preliminary mechanical activation of the powder composition Al + Fe2O3 and the subsequent addition of titanium and soot powders to the product of this treatment. Analysis of the structure formation and mechanical properties of sintered compacts from the studied powder mixtures showed the advantage of the two-stage option in terms of the formation of a denser structure in the samples with minimal residual porosity and higher values of compressive strength. 2026-07-13 JMMP, Vol. 10, Pages 246: The Influence of Mixing Modes on Structure Formation and Mechanical Properties of Ti-Al-Fe-O-C Powder Materials During Vacuum Sintering

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070246

Authors: Elena N. Korosteleva Kirill O. Akimov Andrey I. Dmitriev

One of the possible ways to increase the functional properties of titanium-based composites is the use of additional components in the form of solid inclusions of oxides, carbides, etc. The key task in this case is to achieve a uniform distribution of such inclusions in the structure of the material. This study demonstrates that this problem can be more effectively solved at the stage of preparing the powder mixture from which a titanium matrix composite is subsequently obtained. The paper presents the results of a study of the structure and mechanical properties of sintered powder materials of the Ti-Al-Fe-O-C system using two procedures for mixing the initial components. In the first case, traditional mixing of titanium, aluminum, soot and iron oxide Fe2O3 powders was used, and in the second case, a two-stage procedure was used with preliminary mechanical activation of the powder composition Al + Fe2O3 and the subsequent addition of titanium and soot powders to the product of this treatment. Analysis of the structure formation and mechanical properties of sintered compacts from the studied powder mixtures showed the advantage of the two-stage option in terms of the formation of a denser structure in the samples with minimal residual porosity and higher values of compressive strength.

]]> The Influence of Mixing Modes on Structure Formation and Mechanical Properties of Ti-Al-Fe-O-C Powder Materials During Vacuum Sintering Elena N. Korosteleva Kirill O. Akimov Andrey I. Dmitriev doi: 10.3390/jmmp10070246 Journal of Manufacturing and Materials Processing 2026-07-13 Journal of Manufacturing and Materials Processing 2026-07-13 10 7 Article 246 10.3390/jmmp10070246 https://www.mdpi.com/2504-4494/10/7/246 JMMP, Vol. 10, Pages 245: Research on the Formation Mechanism and Distribution Characteristics of Surface Roughness in End Milling https://www.mdpi.com/2504-4494/10/7/245 The cutting variables of end milling are positively correlated with the machined surface roughness, but their mechanism of action remains unclear. Since the cutting tool used in end milling is a three-dimensional solid, under the action of horizontal cutting force, there exist both axial tensile strain and axial compressive strain in the cutting tool at the same time, thus putting forward an assumption about the formation mechanism of machined surface roughness: cutting variables affect the axial tensile strain of the cutting edge through the horizontal cutting force, and cause the cutting-edge tip to vertically wedge into the machined surface, thereby influencing the unevenness of the processed surface. Based on the cutting-tool deflection model of a two-segment cantilever beam and the horizontal cutting force formula, the mathematical expression for the axial strain at the sharp tip of the cutting edge was derived. Groove milling and half-groove milling experiments were done, and the experimental results show that the roughness Ra value in the central area is significantly higher than that in the cut-in area, with its maximum average value being 1.32 times that of the cut-in area. The surface roughness rises following the rise in depth of machining and feed per cutting tooth, but this relationship is significant. The laboratory findings are consistent with the theoretical analysis results, indicating that the assumption about the formation mechanism of surface roughness should be reasonable, and the surface roughness in the central area is greater than that in the cutting tool cut-in area. The research results provide a kind of new insight into the formation mechanism of machined surface roughness, which can serve as a reference for relevant research and cutting practices. 2026-07-09 JMMP, Vol. 10, Pages 245: Research on the Formation Mechanism and Distribution Characteristics of Surface Roughness in End Milling

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070245

Authors: Can Liu Zhiyi Mo Runhua Lu Jiajia He Ningxia Yin Huanlao Liu

The cutting variables of end milling are positively correlated with the machined surface roughness, but their mechanism of action remains unclear. Since the cutting tool used in end milling is a three-dimensional solid, under the action of horizontal cutting force, there exist both axial tensile strain and axial compressive strain in the cutting tool at the same time, thus putting forward an assumption about the formation mechanism of machined surface roughness: cutting variables affect the axial tensile strain of the cutting edge through the horizontal cutting force, and cause the cutting-edge tip to vertically wedge into the machined surface, thereby influencing the unevenness of the processed surface. Based on the cutting-tool deflection model of a two-segment cantilever beam and the horizontal cutting force formula, the mathematical expression for the axial strain at the sharp tip of the cutting edge was derived. Groove milling and half-groove milling experiments were done, and the experimental results show that the roughness Ra value in the central area is significantly higher than that in the cut-in area, with its maximum average value being 1.32 times that of the cut-in area. The surface roughness rises following the rise in depth of machining and feed per cutting tooth, but this relationship is significant. The laboratory findings are consistent with the theoretical analysis results, indicating that the assumption about the formation mechanism of surface roughness should be reasonable, and the surface roughness in the central area is greater than that in the cutting tool cut-in area. The research results provide a kind of new insight into the formation mechanism of machined surface roughness, which can serve as a reference for relevant research and cutting practices.

]]> Research on the Formation Mechanism and Distribution Characteristics of Surface Roughness in End Milling Can Liu Zhiyi Mo Runhua Lu Jiajia He Ningxia Yin Huanlao Liu doi: 10.3390/jmmp10070245 Journal of Manufacturing and Materials Processing 2026-07-09 Journal of Manufacturing and Materials Processing 2026-07-09 10 7 Article 245 10.3390/jmmp10070245 https://www.mdpi.com/2504-4494/10/7/245 JMMP, Vol. 10, Pages 244: Adapting Laser Ablation Models from Simulation to Experiment: A Transfer Learning Approach for Stainless Steel, Silicon and Aluminum https://www.mdpi.com/2504-4494/10/7/244 Ultrashort Pulse Laser (USPL) ablation is a versatile manufacturing process, but predicting its outcomes across different materials often requires extensive and costly experimentation. This work provides a machine learning framework that leverages transfer learning to bridge the gap between simulation and experimental data, enabling accurate prediction of material behavior during USPL ablation under data-scarce conditions. We generated a high-fidelity computational dataset using the LS-PLUME® simulator for Stainless Steel 316 (SS 316), and then complemented with targeted experimental studies on SS 316, Silicon (Si) and Aluminum (Al) to capture real-world deviations. A model pre-trained on the simulation data was successfully adapted to the experimental domain, effectively absorbing systematic deviations and extending its predictive capability to new materials with minimal experimental data. Our transfer learning framework bridged the simulation-to-experiment gap using minimal data, successfully fine-tuning a base model trained on 3075 samples with just 49 experimental points for Si and 46 for Al with mean percentage errors under 5%, thus demonstrating high data efficiency for industrial laser surface texturing. Furthermore, the application of explainable artificial intelligence revealed that the model predictions are more sensitive to peak fluence and the number of passes, with SS 316 exhibiting higher overall sensitivity to input parameter variations than Si and Al, thus providing actionable physical and process-level insight relevant for industrial optimization. 2026-07-09 JMMP, Vol. 10, Pages 244: Adapting Laser Ablation Models from Simulation to Experiment: A Transfer Learning Approach for Stainless Steel, Silicon and Aluminum

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070244

Authors: Javier F. Troncoso Beatriz Blanco-Filgueira Vanessa Alvear-Puertas Marta Gallego-Vázquez Sara Vidal Tamara Delgado Céline Petit David Bruneel Pablo Romero Santiago Muiños-Landin

Ultrashort Pulse Laser (USPL) ablation is a versatile manufacturing process, but predicting its outcomes across different materials often requires extensive and costly experimentation. This work provides a machine learning framework that leverages transfer learning to bridge the gap between simulation and experimental data, enabling accurate prediction of material behavior during USPL ablation under data-scarce conditions. We generated a high-fidelity computational dataset using the LS-PLUME® simulator for Stainless Steel 316 (SS 316), and then complemented with targeted experimental studies on SS 316, Silicon (Si) and Aluminum (Al) to capture real-world deviations. A model pre-trained on the simulation data was successfully adapted to the experimental domain, effectively absorbing systematic deviations and extending its predictive capability to new materials with minimal experimental data. Our transfer learning framework bridged the simulation-to-experiment gap using minimal data, successfully fine-tuning a base model trained on 3075 samples with just 49 experimental points for Si and 46 for Al with mean percentage errors under 5%, thus demonstrating high data efficiency for industrial laser surface texturing. Furthermore, the application of explainable artificial intelligence revealed that the model predictions are more sensitive to peak fluence and the number of passes, with SS 316 exhibiting higher overall sensitivity to input parameter variations than Si and Al, thus providing actionable physical and process-level insight relevant for industrial optimization.

]]> Adapting Laser Ablation Models from Simulation to Experiment: A Transfer Learning Approach for Stainless Steel, Silicon and Aluminum Javier F. Troncoso Beatriz Blanco-Filgueira Vanessa Alvear-Puertas Marta Gallego-Vázquez Sara Vidal Tamara Delgado Céline Petit David Bruneel Pablo Romero Santiago Muiños-Landin doi: 10.3390/jmmp10070244 Journal of Manufacturing and Materials Processing 2026-07-09 Journal of Manufacturing and Materials Processing 2026-07-09 10 7 Article 244 10.3390/jmmp10070244 https://www.mdpi.com/2504-4494/10/7/244 JMMP, Vol. 10, Pages 243: Effect of GMAW Process Parameters and Filler Alloys on Solidification Cracking and Mechanical Behavior of AA6061 and AA7075 Aluminum Alloys https://www.mdpi.com/2504-4494/10/7/243 This study investigates the effect of Gas Metal Arc Welding (GMAW) parameters on solidification cracking and mechanical behavior of AA6061 and AA7075 aluminum alloys, which are widely used in automotive, aerospace, and battery-related applications due to their low density, corrosion resistance, and high specific strength. The influence of filler metals, ER4043 and ER5356, welding speed, wire feed speed, and calculated heat input was evaluated using the Circular Patch Test (CPT). Surface and internal cracking were examined by X-ray inspection, while microstructural evolution, phase formation, hardness, tensile behavior, and local strain distribution were analyzed using optical microscopy, SEM/EDS, XRD, microhardness testing, micro-tensile testing, and Digital Image Correlation (DIC). The results show that cracking susceptibility depends on the combined effects of welding speed, heat input, filler-metal chemistry, and dilution. The observed cracking behavior is associated with local compositional variations, weld defects, and the formation of low-melting/eutectic or secondary constituents within the fusion zone, rather than being attributed to a single factor. ER5356 showed favorable cracking resistance for AA7075 under the selected conditions, while ER4043 generally improved cracking resistance for AA6061. The mechanical response and fracture behavior were also influenced by filler composition and local weld microstructure. These findings provide useful guidance for selecting welding parameters and filler metals to improve weld quality and reduce solidification cracking in AA6061 and AA7075 aluminum alloys. 2026-07-09 JMMP, Vol. 10, Pages 243: Effect of GMAW Process Parameters and Filler Alloys on Solidification Cracking and Mechanical Behavior of AA6061 and AA7075 Aluminum Alloys

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070243

Authors: Mohammed Alkhabbat Xuan-Tan Pham

This study investigates the effect of Gas Metal Arc Welding (GMAW) parameters on solidification cracking and mechanical behavior of AA6061 and AA7075 aluminum alloys, which are widely used in automotive, aerospace, and battery-related applications due to their low density, corrosion resistance, and high specific strength. The influence of filler metals, ER4043 and ER5356, welding speed, wire feed speed, and calculated heat input was evaluated using the Circular Patch Test (CPT). Surface and internal cracking were examined by X-ray inspection, while microstructural evolution, phase formation, hardness, tensile behavior, and local strain distribution were analyzed using optical microscopy, SEM/EDS, XRD, microhardness testing, micro-tensile testing, and Digital Image Correlation (DIC). The results show that cracking susceptibility depends on the combined effects of welding speed, heat input, filler-metal chemistry, and dilution. The observed cracking behavior is associated with local compositional variations, weld defects, and the formation of low-melting/eutectic or secondary constituents within the fusion zone, rather than being attributed to a single factor. ER5356 showed favorable cracking resistance for AA7075 under the selected conditions, while ER4043 generally improved cracking resistance for AA6061. The mechanical response and fracture behavior were also influenced by filler composition and local weld microstructure. These findings provide useful guidance for selecting welding parameters and filler metals to improve weld quality and reduce solidification cracking in AA6061 and AA7075 aluminum alloys.

]]> Effect of GMAW Process Parameters and Filler Alloys on Solidification Cracking and Mechanical Behavior of AA6061 and AA7075 Aluminum Alloys Mohammed Alkhabbat Xuan-Tan Pham doi: 10.3390/jmmp10070243 Journal of Manufacturing and Materials Processing 2026-07-09 Journal of Manufacturing and Materials Processing 2026-07-09 10 7 Article 243 10.3390/jmmp10070243 https://www.mdpi.com/2504-4494/10/7/243 JMMP, Vol. 10, Pages 242: Development and Performance Analysis of an Automated Flat Blade Grinding Machine for Wood Processing and Plastic Recycling Industries https://www.mdpi.com/2504-4494/10/7/242 This study presents the design, development, and experimental validation of an automated flat blade grinding machine for the wood processing and plastic recycling industries in Ecuador. The machine was engineered following the VDI 2221/2222/2225 design methodology, integrating SolidWorks-based 3D modeling and ANSYS finite element analysis (FEA) to validate critical structural components. The selected configuration includes a Type 6 alumina grinding wheel (38A-60-K-VS), a mechanical clamping system, cutting fluid cooling, and a hardwired electromechanical control system that does not require a programmable logic controller (PLC). FEA results confirmed adequate safety factors (ηs > 16; ηf > 14) for the ACME 3/4–8 power screw under operational loads. Experimental testing on blade specimens (thickness: 3 mm; length: 70 mm; steel up to 60 HRC) demonstrated that four grinding passes at a 45° inclination angle reduced mean surface roughness (Ra) from 5.39 ± 1.83 µm (used blades) to 0.162 ± 0.092 µm, achieving values comparable to new blades (Ra = 0.601 ± 0.153 µm): a point-estimate reduction of 97% in mean Ra relative to the used-blade condition. The automated process reduced average grinding time by approximately 30% compared to manual methods, while maintaining noise levels within the 85 dB occupational exposure limit. Operator satisfaction surveys rated the system above 4.5/5.0 across all ergonomic and usability criteria. These results validate the proposed machine as a cost-effective, locally manufacturable solution to standardize blade maintenance in small and medium enterprises (SMEs) across Latin America. 2026-07-08 JMMP, Vol. 10, Pages 242: Development and Performance Analysis of an Automated Flat Blade Grinding Machine for Wood Processing and Plastic Recycling Industries

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070242

Authors: John Vera Santiago López Carmen Tisalema Marco Zurita

This study presents the design, development, and experimental validation of an automated flat blade grinding machine for the wood processing and plastic recycling industries in Ecuador. The machine was engineered following the VDI 2221/2222/2225 design methodology, integrating SolidWorks-based 3D modeling and ANSYS finite element analysis (FEA) to validate critical structural components. The selected configuration includes a Type 6 alumina grinding wheel (38A-60-K-VS), a mechanical clamping system, cutting fluid cooling, and a hardwired electromechanical control system that does not require a programmable logic controller (PLC). FEA results confirmed adequate safety factors (ηs > 16; ηf > 14) for the ACME 3/4–8 power screw under operational loads. Experimental testing on blade specimens (thickness: 3 mm; length: 70 mm; steel up to 60 HRC) demonstrated that four grinding passes at a 45° inclination angle reduced mean surface roughness (Ra) from 5.39 ± 1.83 µm (used blades) to 0.162 ± 0.092 µm, achieving values comparable to new blades (Ra = 0.601 ± 0.153 µm): a point-estimate reduction of 97% in mean Ra relative to the used-blade condition. The automated process reduced average grinding time by approximately 30% compared to manual methods, while maintaining noise levels within the 85 dB occupational exposure limit. Operator satisfaction surveys rated the system above 4.5/5.0 across all ergonomic and usability criteria. These results validate the proposed machine as a cost-effective, locally manufacturable solution to standardize blade maintenance in small and medium enterprises (SMEs) across Latin America.

]]> Development and Performance Analysis of an Automated Flat Blade Grinding Machine for Wood Processing and Plastic Recycling Industries John Vera Santiago López Carmen Tisalema Marco Zurita doi: 10.3390/jmmp10070242 Journal of Manufacturing and Materials Processing 2026-07-08 Journal of Manufacturing and Materials Processing 2026-07-08 10 7 Article 242 10.3390/jmmp10070242 https://www.mdpi.com/2504-4494/10/7/242 JMMP, Vol. 10, Pages 241: Design and Performance Evaluation of a FSW Tool for Welding of AW 7075-T651 Aluminum Alloy https://www.mdpi.com/2504-4494/10/7/241 Friction stir welding (FSW) is a solid-state joining process capable of producing high-quality joints in materials that are difficult to weld, particularly lightweight alloys. It is especially suitable for high-strength aluminum alloys like AW7075-T651, which are prone to hot cracking and mechanical degradation during conventional fusion welding. The AW7075-T651 alloy is one of the strongest commercially available aluminum alloys, whose high strength is primarily provided by MgZn2 precipitates. The influence of welding parameters, especially welding speed, on heat input was studied using thermocouples positioned beneath the tool shoulder and in the weld root region. Tool lifetime was evaluated using WC-Co probes with different Co content, while tool wear was analyzed by 3D scanning. Microstructural characterization was performed using EBSD and TEM analyses. The maximum tool lifetime reached 2.7 km. Welding speed significantly affected the temperature in the weld root region, and a minimum temperature of 0.58TM was required to produce a sound weld. Weld efficiency of 90% was reached; microhardness profiles showed a typical W-shape. TEM and SAED analyses confirmed the presence of an α-Al matrix and strengthening MgZn2 precipitates and showed a more uniform distribution and refinement of precipitates in the stir zone. 2026-07-07 JMMP, Vol. 10, Pages 241: Design and Performance Evaluation of a FSW Tool for Welding of AW 7075-T651 Aluminum Alloy

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070241

Authors: Roman Kukuča Jozef Bárta Katarína Bártová Ivan Buranský Milan Marônek František Jurina Peter Gogola

Friction stir welding (FSW) is a solid-state joining process capable of producing high-quality joints in materials that are difficult to weld, particularly lightweight alloys. It is especially suitable for high-strength aluminum alloys like AW7075-T651, which are prone to hot cracking and mechanical degradation during conventional fusion welding. The AW7075-T651 alloy is one of the strongest commercially available aluminum alloys, whose high strength is primarily provided by MgZn2 precipitates. The influence of welding parameters, especially welding speed, on heat input was studied using thermocouples positioned beneath the tool shoulder and in the weld root region. Tool lifetime was evaluated using WC-Co probes with different Co content, while tool wear was analyzed by 3D scanning. Microstructural characterization was performed using EBSD and TEM analyses. The maximum tool lifetime reached 2.7 km. Welding speed significantly affected the temperature in the weld root region, and a minimum temperature of 0.58TM was required to produce a sound weld. Weld efficiency of 90% was reached; microhardness profiles showed a typical W-shape. TEM and SAED analyses confirmed the presence of an α-Al matrix and strengthening MgZn2 precipitates and showed a more uniform distribution and refinement of precipitates in the stir zone.

]]> Design and Performance Evaluation of a FSW Tool for Welding of AW 7075-T651 Aluminum Alloy Roman Kukuča Jozef Bárta Katarína Bártová Ivan Buranský Milan Marônek František Jurina Peter Gogola doi: 10.3390/jmmp10070241 Journal of Manufacturing and Materials Processing 2026-07-07 Journal of Manufacturing and Materials Processing 2026-07-07 10 7 Article 241 10.3390/jmmp10070241 https://www.mdpi.com/2504-4494/10/7/241 JMMP, Vol. 10, Pages 240: Spatter, Melt Pool Stability, and Their Correlations Using Deep Learning for Laser Directed Energy Deposition https://www.mdpi.com/2504-4494/10/7/240 Laser directed energy deposition (LDED) is a promising metal additive manufacturing process, but printed parts’ quality highly depends on spatter formation and melt pool stability. In this work, a high-speed camera is employed to capture and record the complex interaction between the laser, fed powders, and fusion region under various LDED process conditions. A deep learning algorithm, the YOLOv7 model, is trained to automatically detect and track the location and motion of the melt pool and spatter particles. The well-trained YOLOv7 model achieves a precision of 0.94 and is then applied to extract information on spatter count, spatter size, and melt pool geometry. We find that an elevated laser power intensifies spatter formation due to augmented vapor recoil pressure, while a high scanning speed promotes spatter ejection through Plateau–Rayleigh capillary instability. A low powder feed rate further exacerbates spatter formation owing to high metal evaporation and hydrodynamic instability within the small melt pool. In addition, this work introduces a novel melt pool stability index for real-time process assessment based on the melt pool length change rate. A stable melt pool with a high stability index generates less spatter. Otherwise, more spatters are detected. These findings advance the mechanistic understanding of spatter dynamics in LDED, introduce a novel quantitative metric for real-time melt pool stability assessment, and establish a direct correlation between the detected spatter amount and the melt pool stability. This work provides a practical framework for spatter mitigation, melt pool stability enhancement, and in-process control in advanced manufacturing. 2026-07-07 JMMP, Vol. 10, Pages 240: Spatter, Melt Pool Stability, and Their Correlations Using Deep Learning for Laser Directed Energy Deposition

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070240

Authors: Md Sakibul Hasan Nahid Deepak Gadde Jakob D. Hamilton Shan Jiang Yang Du

Laser directed energy deposition (LDED) is a promising metal additive manufacturing process, but printed parts’ quality highly depends on spatter formation and melt pool stability. In this work, a high-speed camera is employed to capture and record the complex interaction between the laser, fed powders, and fusion region under various LDED process conditions. A deep learning algorithm, the YOLOv7 model, is trained to automatically detect and track the location and motion of the melt pool and spatter particles. The well-trained YOLOv7 model achieves a precision of 0.94 and is then applied to extract information on spatter count, spatter size, and melt pool geometry. We find that an elevated laser power intensifies spatter formation due to augmented vapor recoil pressure, while a high scanning speed promotes spatter ejection through Plateau–Rayleigh capillary instability. A low powder feed rate further exacerbates spatter formation owing to high metal evaporation and hydrodynamic instability within the small melt pool. In addition, this work introduces a novel melt pool stability index for real-time process assessment based on the melt pool length change rate. A stable melt pool with a high stability index generates less spatter. Otherwise, more spatters are detected. These findings advance the mechanistic understanding of spatter dynamics in LDED, introduce a novel quantitative metric for real-time melt pool stability assessment, and establish a direct correlation between the detected spatter amount and the melt pool stability. This work provides a practical framework for spatter mitigation, melt pool stability enhancement, and in-process control in advanced manufacturing.

]]> Spatter, Melt Pool Stability, and Their Correlations Using Deep Learning for Laser Directed Energy Deposition Md Sakibul Hasan Nahid Deepak Gadde Jakob D. Hamilton Shan Jiang Yang Du doi: 10.3390/jmmp10070240 Journal of Manufacturing and Materials Processing 2026-07-07 Journal of Manufacturing and Materials Processing 2026-07-07 10 7 Article 240 10.3390/jmmp10070240 https://www.mdpi.com/2504-4494/10/7/240 JMMP, Vol. 10, Pages 239: Development of Microwave Attenuator Based on Magnetic Composites and Frequency Selective Surface (FSS) in the X-Band Using FEKO https://www.mdpi.com/2504-4494/10/7/239 The development of a magnetic composite based on a silicone matrix containing carbonyl iron (CI), combined with the Frequency Selective Surface (FSS) for radiation-attenuating material (RAM) applications in the X-band (8.2–12.4 GHz), is presented in this work. Four FSS geometries were investigated: square, circular, triangular, and hexagonal. The electromagnetic properties, namely relative electrical permittivity and magnetic permeability, were characterized using a vector network analyzer employing both waveguide and free-space measurement techniques. The attenuation performance was evaluated through reflection loss (RL) measurements and numerically simulated using FEKO software. The stability of the attenuation performance was also assessed for different wave incidence angles (0° to 45°), demonstrating a robust average peak attenuation of −32.1 dB at 11.18 GHz, with optimal resonance values reaching as low as −60.34 dB at an incidence angle of 30°, in good agreement with the simulation results. The results indicate that the capacitive and inductive behavior associated with FSS geometries plays a key role in tailoring the electromagnetic response, demonstrating the effectiveness of FSS-based magnetic composites for controlled attenuation performance. 2026-07-07 JMMP, Vol. 10, Pages 239: Development of Microwave Attenuator Based on Magnetic Composites and Frequency Selective Surface (FSS) in the X-Band Using FEKO

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070239

Authors: Braulio Haruo Kondo Lopes Felipe de Moraes Yamamoto Giovana Silva Cembranelli Isaias De Oliveira Carlos Eduardo Santos Leal Fabio Roberto Passador Mauricio Ribeiro Baldan

The development of a magnetic composite based on a silicone matrix containing carbonyl iron (CI), combined with the Frequency Selective Surface (FSS) for radiation-attenuating material (RAM) applications in the X-band (8.2–12.4 GHz), is presented in this work. Four FSS geometries were investigated: square, circular, triangular, and hexagonal. The electromagnetic properties, namely relative electrical permittivity and magnetic permeability, were characterized using a vector network analyzer employing both waveguide and free-space measurement techniques. The attenuation performance was evaluated through reflection loss (RL) measurements and numerically simulated using FEKO software. The stability of the attenuation performance was also assessed for different wave incidence angles (0° to 45°), demonstrating a robust average peak attenuation of −32.1 dB at 11.18 GHz, with optimal resonance values reaching as low as −60.34 dB at an incidence angle of 30°, in good agreement with the simulation results. The results indicate that the capacitive and inductive behavior associated with FSS geometries plays a key role in tailoring the electromagnetic response, demonstrating the effectiveness of FSS-based magnetic composites for controlled attenuation performance.

]]> Development of Microwave Attenuator Based on Magnetic Composites and Frequency Selective Surface (FSS) in the X-Band Using FEKO Braulio Haruo Kondo Lopes Felipe de Moraes Yamamoto Giovana Silva Cembranelli Isaias De Oliveira Carlos Eduardo Santos Leal Fabio Roberto Passador Mauricio Ribeiro Baldan doi: 10.3390/jmmp10070239 Journal of Manufacturing and Materials Processing 2026-07-07 Journal of Manufacturing and Materials Processing 2026-07-07 10 7 Article 239 10.3390/jmmp10070239 https://www.mdpi.com/2504-4494/10/7/239 JMMP, Vol. 10, Pages 238: Recent Advances in Ultrasonic Vibration-Assisted Machining of Ti-Al Intermetallic Compounds https://www.mdpi.com/2504-4494/10/7/238 Ti-Al intermetallic compounds (Ti-Al IMCs) are emerging as lightweight, high-temperature structural materials with considerable application potential. Owing to their low density and high-temperature capability, these materials can improve the thrust-to-weight ratio of aeroengines, enhance the high-temperature service performance of aircraft, increase fuel efficiency, and improve adaptability to harsh environments. However, their intrinsic room-temperature brittleness leads to high cutting forces, elevated cutting temperatures, and severe tool wear during machining, making it difficult to ensure machining quality and limiting their large-scale applications in the aerospace industry. Ultrasonic vibration-assisted machining (UVAM) introduces a high-frequency, low-amplitude intermittent cutting mechanism that actively regulates material removal and offers a feasible route for overcoming the machining bottleneck of Ti-Al IMCs. This review summarizes the recent progress in UVAM for machining Ti-Al IMCs. First, the typical applications and machining characteristics of Ti-Al IMCs are discussed. Existing studies are then reviewed in terms of cutting performance, including cutting force, cutting temperature, chip morphology, tool wear, and post-machining surface integrity, including surface roughness, surface defects, residual stress, and work hardening. The reviewed evidence indicates that UVAM can reduce cutting forces and temperatures, improve chip morphology, and extend the tool life. It can also improve machined surface integrity by decreasing surface roughness, suppressing surface defects, inducing beneficial residual compressive stress layers, and regulating work-hardening behavior. This review provides systematic theoretical guidance and technical references for improving the machinability of Ti-Al IMCs via UVAM, thereby enabling the controllable, high-performance, and high-reliability fabrication of these difficult-to-machine materials in aerospace precision manufacturing. 2026-07-06 JMMP, Vol. 10, Pages 238: Recent Advances in Ultrasonic Vibration-Assisted Machining of Ti-Al Intermetallic Compounds

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070238

Authors: Zongxia Fu Xuansheng Zhao Haichao Sun Xiaofeng Jia

Ti-Al intermetallic compounds (Ti-Al IMCs) are emerging as lightweight, high-temperature structural materials with considerable application potential. Owing to their low density and high-temperature capability, these materials can improve the thrust-to-weight ratio of aeroengines, enhance the high-temperature service performance of aircraft, increase fuel efficiency, and improve adaptability to harsh environments. However, their intrinsic room-temperature brittleness leads to high cutting forces, elevated cutting temperatures, and severe tool wear during machining, making it difficult to ensure machining quality and limiting their large-scale applications in the aerospace industry. Ultrasonic vibration-assisted machining (UVAM) introduces a high-frequency, low-amplitude intermittent cutting mechanism that actively regulates material removal and offers a feasible route for overcoming the machining bottleneck of Ti-Al IMCs. This review summarizes the recent progress in UVAM for machining Ti-Al IMCs. First, the typical applications and machining characteristics of Ti-Al IMCs are discussed. Existing studies are then reviewed in terms of cutting performance, including cutting force, cutting temperature, chip morphology, tool wear, and post-machining surface integrity, including surface roughness, surface defects, residual stress, and work hardening. The reviewed evidence indicates that UVAM can reduce cutting forces and temperatures, improve chip morphology, and extend the tool life. It can also improve machined surface integrity by decreasing surface roughness, suppressing surface defects, inducing beneficial residual compressive stress layers, and regulating work-hardening behavior. This review provides systematic theoretical guidance and technical references for improving the machinability of Ti-Al IMCs via UVAM, thereby enabling the controllable, high-performance, and high-reliability fabrication of these difficult-to-machine materials in aerospace precision manufacturing.

]]> Recent Advances in Ultrasonic Vibration-Assisted Machining of Ti-Al Intermetallic Compounds Zongxia Fu Xuansheng Zhao Haichao Sun Xiaofeng Jia doi: 10.3390/jmmp10070238 Journal of Manufacturing and Materials Processing 2026-07-06 Journal of Manufacturing and Materials Processing 2026-07-06 10 7 Review 238 10.3390/jmmp10070238 https://www.mdpi.com/2504-4494/10/7/238 JMMP, Vol. 10, Pages 237: Optimization of Technological Processes on CNC Lathes with Robotic Loading https://www.mdpi.com/2504-4494/10/7/237 The article presents a methodology for multi-objective compromise optimization of the process of turning on CNC machines with robotic loading by the methods of determining the optimum compromise area and carrying out optimization, using the generalized arithmetic mean utility function with weight coefficients. The methodology has been applied to determine the optimal cutting conditions, ensuring the best combination of technological parameters for the CNC turning process when machining parts made of 42CrMoS4 steel with cutting tools from different manufacturers. A complex study and modeling of the main technological parameters (production rate, cutting tool lifetime, and roughness of machined surfaces) in the CNC turning process have been performed depending on the conditions of cutting. By applying a genetic algorithm, the optimal conditions for implementing the process using both optimization methods have been determined, and a comparative analysis of the technological parameters has been made. Models have been created for predicting the number of machined parts, which exclude unplanned stops for tool changes, under the specified optimal conditions of cutting, taking into account the capacity of the tool magazine, the loading mechanism, and the volume of the production batch. 2026-07-06 JMMP, Vol. 10, Pages 237: Optimization of Technological Processes on CNC Lathes with Robotic Loading

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070237

Authors: Irina Aleksandrova Hristo Metev Nikolai Kolev Hristian Mitev

The article presents a methodology for multi-objective compromise optimization of the process of turning on CNC machines with robotic loading by the methods of determining the optimum compromise area and carrying out optimization, using the generalized arithmetic mean utility function with weight coefficients. The methodology has been applied to determine the optimal cutting conditions, ensuring the best combination of technological parameters for the CNC turning process when machining parts made of 42CrMoS4 steel with cutting tools from different manufacturers. A complex study and modeling of the main technological parameters (production rate, cutting tool lifetime, and roughness of machined surfaces) in the CNC turning process have been performed depending on the conditions of cutting. By applying a genetic algorithm, the optimal conditions for implementing the process using both optimization methods have been determined, and a comparative analysis of the technological parameters has been made. Models have been created for predicting the number of machined parts, which exclude unplanned stops for tool changes, under the specified optimal conditions of cutting, taking into account the capacity of the tool magazine, the loading mechanism, and the volume of the production batch.

]]> Optimization of Technological Processes on CNC Lathes with Robotic Loading Irina Aleksandrova Hristo Metev Nikolai Kolev Hristian Mitev doi: 10.3390/jmmp10070237 Journal of Manufacturing and Materials Processing 2026-07-06 Journal of Manufacturing and Materials Processing 2026-07-06 10 7 Article 237 10.3390/jmmp10070237 https://www.mdpi.com/2504-4494/10/7/237 JMMP, Vol. 10, Pages 236: Development of Conductive Nanocomposite Filaments from Reused Selective Laser Sintering Powder for Fused Filament Fabrication https://www.mdpi.com/2504-4494/10/7/236 In polymer selective laser sintering (SLS), powder acts as a support material during additive manufacturing, generating significant amounts of un-sintered powder exposed to prolonged thermal cycles. Although partial reuse with virgin powder is common practice, material degradation eventually renders the powder unsuitable for further SLS processing. This study investigates a sustainable approach for valorising SLS waste powder through its conversion into filament feedstock for fused filament fabrication (FFF). Polyamide 12 filaments containing 0, 2, 3, and 4 wt.% multi-walled carbon nanotubes (MWCNTs) were produced by twin-screw extrusion to tailor the electrical conductivity of the polymer matrix. The filaments were processed by FFF to manufacture specimens for thermal, mechanical, and electrical characterization. Differential scanning calorimetry revealed the influence of reprocessing on the thermal behaviour of the reused material and resulting filaments, while thermogravimetric analysis demonstrated improved thermal stability with increasing MWCNT content. Tensile testing showed increased Young’s modulus (up to 9.4%), despite an initial drop, and tensile stress at break (up to 56.3%) with increasing nanofiller concentration. In addition, distinct electrostatic-discharge (ESD) protection ranges were achieved depending on the MWCNT loading. The results demonstrate the potential of reused SLS powder as a sustainable feedstock for functional AM materials suitable for ESD-sensitive applications. 2026-07-04 JMMP, Vol. 10, Pages 236: Development of Conductive Nanocomposite Filaments from Reused Selective Laser Sintering Powder for Fused Filament Fabrication

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070236

Authors: Cátia S. Silva Ana C. Lopes Álvaro M. Sampaio António J. Pontes

In polymer selective laser sintering (SLS), powder acts as a support material during additive manufacturing, generating significant amounts of un-sintered powder exposed to prolonged thermal cycles. Although partial reuse with virgin powder is common practice, material degradation eventually renders the powder unsuitable for further SLS processing. This study investigates a sustainable approach for valorising SLS waste powder through its conversion into filament feedstock for fused filament fabrication (FFF). Polyamide 12 filaments containing 0, 2, 3, and 4 wt.% multi-walled carbon nanotubes (MWCNTs) were produced by twin-screw extrusion to tailor the electrical conductivity of the polymer matrix. The filaments were processed by FFF to manufacture specimens for thermal, mechanical, and electrical characterization. Differential scanning calorimetry revealed the influence of reprocessing on the thermal behaviour of the reused material and resulting filaments, while thermogravimetric analysis demonstrated improved thermal stability with increasing MWCNT content. Tensile testing showed increased Young’s modulus (up to 9.4%), despite an initial drop, and tensile stress at break (up to 56.3%) with increasing nanofiller concentration. In addition, distinct electrostatic-discharge (ESD) protection ranges were achieved depending on the MWCNT loading. The results demonstrate the potential of reused SLS powder as a sustainable feedstock for functional AM materials suitable for ESD-sensitive applications.

]]> Development of Conductive Nanocomposite Filaments from Reused Selective Laser Sintering Powder for Fused Filament Fabrication Cátia S. Silva Ana C. Lopes Álvaro M. Sampaio António J. Pontes doi: 10.3390/jmmp10070236 Journal of Manufacturing and Materials Processing 2026-07-04 Journal of Manufacturing and Materials Processing 2026-07-04 10 7 Article 236 10.3390/jmmp10070236 https://www.mdpi.com/2504-4494/10/7/236 JMMP, Vol. 10, Pages 235: Multi-Objective Optimization of the Geometry of a Modular Friction Disk Cutter for Thermo-Friction Processing of Spur Gear Teeth https://www.mdpi.com/2504-4494/10/7/235 This study presents multi-objective geometric optimization of a modular friction disk cutter for spur gear thermo-friction processing within the ANSYS Workbench 2024 R1. The integrated workflow—Geometry → Steady-State Thermal → Static Structural → Design of Experiments → Response Surface → Response Surface Optimization—enables selection of a rational tool geometry within a single parametric model. Variable dimensions (a, b, c) describe the load-bearing part: a characterizes the transitional thin profile zone, b is the massive supporting part, and c is the intermediate disk thickness controlling thermo-mechanical load transmission. Dimension c most significantly influences equivalent stresses and directional deformation, while maximum temperature depends on combined a and c effects. Based on Response Surface Optimization, the rational solution domain is concentrated near a≈3 mm, b≈10 mm, and c≈4 mm, yielding P4≈33.306 MPa, P5≈295.93 °C, and P6≈−5.7488·10−5 m. These values demonstrate a sufficient calculated safety margin within the finite element framework, providing a technically justified direction for prototype manufacturing. Although currently evaluated as purely computational without direct full-scale physical measurements, these results establish a foundation for subsequent experimental validation using thermal imaging and optical deformation analysis. Future research will focus on transient thermo-mechanical modeling with impulse cooling and experimental verification. 2026-07-03 JMMP, Vol. 10, Pages 235: Multi-Objective Optimization of the Geometry of a Modular Friction Disk Cutter for Thermo-Friction Processing of Spur Gear Teeth

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070235

Authors: Ansagan Suleimenov Karibek Sherov Assylbek Kassenov Assylkhan Mazdubay Jamshid Ravshanov Doniyor Isaev Musurmon Juraev Gulerke Tattimbek Sayagul Tussupova Davran Radjibaev Zhanara Mussina

This study presents multi-objective geometric optimization of a modular friction disk cutter for spur gear thermo-friction processing within the ANSYS Workbench 2024 R1. The integrated workflow—Geometry → Steady-State Thermal → Static Structural → Design of Experiments → Response Surface → Response Surface Optimization—enables selection of a rational tool geometry within a single parametric model. Variable dimensions (a, b, c) describe the load-bearing part: a characterizes the transitional thin profile zone, b is the massive supporting part, and c is the intermediate disk thickness controlling thermo-mechanical load transmission. Dimension c most significantly influences equivalent stresses and directional deformation, while maximum temperature depends on combined a and c effects. Based on Response Surface Optimization, the rational solution domain is concentrated near a≈3 mm, b≈10 mm, and c≈4 mm, yielding P4≈33.306 MPa, P5≈295.93 °C, and P6≈−5.7488·10−5 m. These values demonstrate a sufficient calculated safety margin within the finite element framework, providing a technically justified direction for prototype manufacturing. Although currently evaluated as purely computational without direct full-scale physical measurements, these results establish a foundation for subsequent experimental validation using thermal imaging and optical deformation analysis. Future research will focus on transient thermo-mechanical modeling with impulse cooling and experimental verification.

]]> Multi-Objective Optimization of the Geometry of a Modular Friction Disk Cutter for Thermo-Friction Processing of Spur Gear Teeth Ansagan Suleimenov Karibek Sherov Assylbek Kassenov Assylkhan Mazdubay Jamshid Ravshanov Doniyor Isaev Musurmon Juraev Gulerke Tattimbek Sayagul Tussupova Davran Radjibaev Zhanara Mussina doi: 10.3390/jmmp10070235 Journal of Manufacturing and Materials Processing 2026-07-03 Journal of Manufacturing and Materials Processing 2026-07-03 10 7 Article 235 10.3390/jmmp10070235 https://www.mdpi.com/2504-4494/10/7/235 JMMP, Vol. 10, Pages 234: Study on the Synergistic Effects of Pre-Deformation and Post-Aging Treatments on the Mechanical and Corrosion Properties of a 2A97 Al-Cu-Li Alloy https://www.mdpi.com/2504-4494/10/7/234 This work systematically investigates the effects of pre-deformation, post-aging temperature, and aging time on the mechanical properties, corrosion behavior, and microstructure of a 2A97 Al-Cu-Li alloy. Microstructural characterization indicates that the main precipitates are T1 (Al2CuLi), δ′ (Al3Li), θ′ (Al2Cu), and S′ (Al2CuMg). At 160 °C with 0% pre-deformation strain, increasing aging time increases the size and number density of T1, changing the size and number density of δ′ and θ′ accordingly, whereas raising the aging temperature to 180 °C mainly coarsens precipitates. Increasing pre-deformation from 0% to 12% increases T1 number density and refines its size. Significantly, after aging at 180 °C, θ′ is absent in the 8% and 12% pre-deformed alloys, and T1 re-dissolves in the over-aged 12% alloy. Grain-boundary (GB) phases evolve from fine/discontinuous (under-aged) to fine/continuous (peak-aged) to coarse/discontinuous (over-aged). At the same time, higher pre-strain reduces their size, and higher aging temperature promotes coarsening. Higher aging temperature and pre-deformation accelerate age hardening and shorten the peak-aging time. In the peak-aged state, strength increases but elongation decreases with increasing pre-deformation or aging temperature. Among all, the 4% pre-deformed alloy aged at 160 °C for 30 h shows optimal room-temperature properties, i.e., ultimate tensile strength ~613 MPa, yield strength ~564 MPa, and total elongation ~6.91%. Corrosion resistance was closely related to microstructural evolution during aging, and both prolonged aging and increased pre-deformation decreased the susceptibility to intergranular corrosion. The results provide a basis for optimizing the thermomechanical processing of 2A97 Al-Cu-Li alloys. 2026-07-02 JMMP, Vol. 10, Pages 234: Study on the Synergistic Effects of Pre-Deformation and Post-Aging Treatments on the Mechanical and Corrosion Properties of a 2A97 Al-Cu-Li Alloy

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070234

Authors: Danyang Liu Bangguo Wu Xin Liu Li Wang Hua Zhou Lei Tang Kefu Gan Jinfeng Li

This work systematically investigates the effects of pre-deformation, post-aging temperature, and aging time on the mechanical properties, corrosion behavior, and microstructure of a 2A97 Al-Cu-Li alloy. Microstructural characterization indicates that the main precipitates are T1 (Al2CuLi), δ′ (Al3Li), θ′ (Al2Cu), and S′ (Al2CuMg). At 160 °C with 0% pre-deformation strain, increasing aging time increases the size and number density of T1, changing the size and number density of δ′ and θ′ accordingly, whereas raising the aging temperature to 180 °C mainly coarsens precipitates. Increasing pre-deformation from 0% to 12% increases T1 number density and refines its size. Significantly, after aging at 180 °C, θ′ is absent in the 8% and 12% pre-deformed alloys, and T1 re-dissolves in the over-aged 12% alloy. Grain-boundary (GB) phases evolve from fine/discontinuous (under-aged) to fine/continuous (peak-aged) to coarse/discontinuous (over-aged). At the same time, higher pre-strain reduces their size, and higher aging temperature promotes coarsening. Higher aging temperature and pre-deformation accelerate age hardening and shorten the peak-aging time. In the peak-aged state, strength increases but elongation decreases with increasing pre-deformation or aging temperature. Among all, the 4% pre-deformed alloy aged at 160 °C for 30 h shows optimal room-temperature properties, i.e., ultimate tensile strength ~613 MPa, yield strength ~564 MPa, and total elongation ~6.91%. Corrosion resistance was closely related to microstructural evolution during aging, and both prolonged aging and increased pre-deformation decreased the susceptibility to intergranular corrosion. The results provide a basis for optimizing the thermomechanical processing of 2A97 Al-Cu-Li alloys.

]]> Study on the Synergistic Effects of Pre-Deformation and Post-Aging Treatments on the Mechanical and Corrosion Properties of a 2A97 Al-Cu-Li Alloy Danyang Liu Bangguo Wu Xin Liu Li Wang Hua Zhou Lei Tang Kefu Gan Jinfeng Li doi: 10.3390/jmmp10070234 Journal of Manufacturing and Materials Processing 2026-07-02 Journal of Manufacturing and Materials Processing 2026-07-02 10 7 Article 234 10.3390/jmmp10070234 https://www.mdpi.com/2504-4494/10/7/234 JMMP, Vol. 10, Pages 233: High-Throughput Fused Filament Fabrication of PLA: Effects of Melting Zone Length and Filament Diameter on Extrusion Force and Volumetric Flow Rate https://www.mdpi.com/2504-4494/10/7/233 Fused filament fabrication (FFF) is a widely used additive manufacturing method in which the process forces within the hotend play an important role in terms of print quality and speed, particularly in high-throughput applications. This work reports on the influence of filament diameter, melting zone length, and nozzle set temperature on the process forces and the maximum achievable volumetric flow rate. Experimental measurements were carried out using a test rig that integrates a load cell to capture the resulting forces, complemented by non-isothermal numerical simulations. The results show that increasing the melting zone length reduces process forces and increases the attainable volumetric flow rate at high feed rates, as the filament has more time to melt. However, the effect depends strongly on filament diameter. For a diameter of 2.85 mm, extending the melting zone leads to a monotonic increase in the maximum achievable flow rate across the entire investigated range. For a diameter of 1.75 mm, an optimum is observed at an intermediate melting zone length, beyond which additional flow resistance outweighs the benefit of improved melting and thus reduces the attainable flow rate. When normalizing for the maximum transferable extruder force, the smaller filament diameter consistently yields superior throughput performance. The simulations reproduce the experimentally observed trends well and support the interpretation that throughput is limited by the competition between heat-transfer-controlled melting and viscous pressure losses. 2026-07-01 JMMP, Vol. 10, Pages 233: High-Throughput Fused Filament Fabrication of PLA: Effects of Melting Zone Length and Filament Diameter on Extrusion Force and Volumetric Flow Rate

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070233

Authors: Philipp Wüst Julian Kattinger Frederik Dahmen Dieter Spiehl Christian Bonten Andreas Blaeser

Fused filament fabrication (FFF) is a widely used additive manufacturing method in which the process forces within the hotend play an important role in terms of print quality and speed, particularly in high-throughput applications. This work reports on the influence of filament diameter, melting zone length, and nozzle set temperature on the process forces and the maximum achievable volumetric flow rate. Experimental measurements were carried out using a test rig that integrates a load cell to capture the resulting forces, complemented by non-isothermal numerical simulations. The results show that increasing the melting zone length reduces process forces and increases the attainable volumetric flow rate at high feed rates, as the filament has more time to melt. However, the effect depends strongly on filament diameter. For a diameter of 2.85 mm, extending the melting zone leads to a monotonic increase in the maximum achievable flow rate across the entire investigated range. For a diameter of 1.75 mm, an optimum is observed at an intermediate melting zone length, beyond which additional flow resistance outweighs the benefit of improved melting and thus reduces the attainable flow rate. When normalizing for the maximum transferable extruder force, the smaller filament diameter consistently yields superior throughput performance. The simulations reproduce the experimentally observed trends well and support the interpretation that throughput is limited by the competition between heat-transfer-controlled melting and viscous pressure losses.

]]> High-Throughput Fused Filament Fabrication of PLA: Effects of Melting Zone Length and Filament Diameter on Extrusion Force and Volumetric Flow Rate Philipp Wüst Julian Kattinger Frederik Dahmen Dieter Spiehl Christian Bonten Andreas Blaeser doi: 10.3390/jmmp10070233 Journal of Manufacturing and Materials Processing 2026-07-01 Journal of Manufacturing and Materials Processing 2026-07-01 10 7 Article 233 10.3390/jmmp10070233 https://www.mdpi.com/2504-4494/10/7/233 JMMP, Vol. 10, Pages 232: Optimization of Robotic Laser Brazing for Electrolytically Galvanized DC06 Steel Under Prototype Production Conditions https://www.mdpi.com/2504-4494/10/7/232 Laser brazing is commonly used for joining visible automotive body panels where both mechanical integrity and surface quality are required. The present work addresses optimization of a robotic laser brazing workstation intended for prototype vehicle production. During initial commissioning, irregular braze formation was associated with unstable filler wire feeding. Therefore, the wire feeding system was modified and subsequently evaluated together with the influence of laser power and wire feed speed on joint quality under a constant robot travel speed. Experimental joints were produced from electrolytically galvanized DC06 steel using CuSi3Mn1 filler wire. Joint performance was assessed by tensile testing and metallographic examination. Tensile strengths between 293 and 314 MPa were obtained, while fracture occurred exclusively in the base material outside the brazed region. Metallographic observations revealed regular braze geometry for parameter sets A, B and D, whereas excessive thermal input resulted in blowhole formation, zinc coating degradation and enlargement of the heat-affected zone. Quantitative evaluation showed a nearly linear increase in the HAZ area with increasing delivered energy (R2 = 0.982). The results indicate that stable brazing conditions can be achieved through an appropriate balance between laser power and wire feed speed under constant robot travel speed conditions. The proposed parameter limits may serve as a practical guideline for robotic laser brazing of thin galvanized automotive sheets under prototype production conditions. 2026-06-30 JMMP, Vol. 10, Pages 232: Optimization of Robotic Laser Brazing for Electrolytically Galvanized DC06 Steel Under Prototype Production Conditions

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070232

Authors: Dušan Sabadka Janette Brezinová Ján Viňáš Jakub Brezina Štefan Novotný

Laser brazing is commonly used for joining visible automotive body panels where both mechanical integrity and surface quality are required. The present work addresses optimization of a robotic laser brazing workstation intended for prototype vehicle production. During initial commissioning, irregular braze formation was associated with unstable filler wire feeding. Therefore, the wire feeding system was modified and subsequently evaluated together with the influence of laser power and wire feed speed on joint quality under a constant robot travel speed. Experimental joints were produced from electrolytically galvanized DC06 steel using CuSi3Mn1 filler wire. Joint performance was assessed by tensile testing and metallographic examination. Tensile strengths between 293 and 314 MPa were obtained, while fracture occurred exclusively in the base material outside the brazed region. Metallographic observations revealed regular braze geometry for parameter sets A, B and D, whereas excessive thermal input resulted in blowhole formation, zinc coating degradation and enlargement of the heat-affected zone. Quantitative evaluation showed a nearly linear increase in the HAZ area with increasing delivered energy (R2 = 0.982). The results indicate that stable brazing conditions can be achieved through an appropriate balance between laser power and wire feed speed under constant robot travel speed conditions. The proposed parameter limits may serve as a practical guideline for robotic laser brazing of thin galvanized automotive sheets under prototype production conditions.

]]> Optimization of Robotic Laser Brazing for Electrolytically Galvanized DC06 Steel Under Prototype Production Conditions Dušan Sabadka Janette Brezinová Ján Viňáš Jakub Brezina Štefan Novotný doi: 10.3390/jmmp10070232 Journal of Manufacturing and Materials Processing 2026-06-30 Journal of Manufacturing and Materials Processing 2026-06-30 10 7 Article 232 10.3390/jmmp10070232 https://www.mdpi.com/2504-4494/10/7/232 JMMP, Vol. 10, Pages 231: Effects of HFMI Treatment on the Boron-Alloyed Austenite Medium-Manganese Steel 140Mn6Cr3TiB Deposit: Enhanced Wear Resistance Induced by Heterogeneous Microstructure https://www.mdpi.com/2504-4494/10/7/231 This paper aims to analyse the microstructure and properties of the titanium- and boron-alloyed high-carbon medium-manganese 140Mn6Cr3TiB steel deposit before and after high-frequency mechanical impact (HFMI) treatment. XRD, SED, and EDS analyses were applied to evaluate the microstructural peculiarities of the studied deposit. Nanoindentation and scratch/sliding tests respectively revealed distinct correlations between the phase composition and the deformation/wear behaviour. HFMI results in the formation of the strain-induced ε- and α’-martensites (~66% and 3–6%, respectively), a significant grains/crystallites refinement (down to 31–54 nm), and dislocation density, which support essential hardening (by ~50%). The HFMI regime (load = 100 N, amplitude = 10 µm, and time = 60 s) was found to be the best, which led to the enhanced wear resistance (decreased wear volume) by ~4 times. The heterogeneous nature of the steel deposit creates a “shield-and-buffer” effect, where the hard eutectic framework resists penetration and tough matrix prevents brittle failure, maintaining a high tolerance to abrasion damage. The HFMI-hardening changed the wear mechanism from the ‘wedge/pile-up’ formation to ploughing. Thus, the HFMI shows a good efficiency in finishing the protective medium-manganese steel deposits of enhanced wear resistance to prolong the operation life of responsible parts. 2026-06-30 JMMP, Vol. 10, Pages 231: Effects of HFMI Treatment on the Boron-Alloyed Austenite Medium-Manganese Steel 140Mn6Cr3TiB Deposit: Enhanced Wear Resistance Induced by Heterogeneous Microstructure

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070231

Authors: Bohdan Trembach Bohdan Mordyuk Michal Krbata Pavlo Openko Vadim Zakiev Vladyslav Shyvaniuk Tetyana Vladimirova Mykola Skoryk Oleksii Kolomiitsev Vadym Krykun Yuliia Musairova Olga Gyrka

This paper aims to analyse the microstructure and properties of the titanium- and boron-alloyed high-carbon medium-manganese 140Mn6Cr3TiB steel deposit before and after high-frequency mechanical impact (HFMI) treatment. XRD, SED, and EDS analyses were applied to evaluate the microstructural peculiarities of the studied deposit. Nanoindentation and scratch/sliding tests respectively revealed distinct correlations between the phase composition and the deformation/wear behaviour. HFMI results in the formation of the strain-induced ε- and α’-martensites (~66% and 3–6%, respectively), a significant grains/crystallites refinement (down to 31–54 nm), and dislocation density, which support essential hardening (by ~50%). The HFMI regime (load = 100 N, amplitude = 10 µm, and time = 60 s) was found to be the best, which led to the enhanced wear resistance (decreased wear volume) by ~4 times. The heterogeneous nature of the steel deposit creates a “shield-and-buffer” effect, where the hard eutectic framework resists penetration and tough matrix prevents brittle failure, maintaining a high tolerance to abrasion damage. The HFMI-hardening changed the wear mechanism from the ‘wedge/pile-up’ formation to ploughing. Thus, the HFMI shows a good efficiency in finishing the protective medium-manganese steel deposits of enhanced wear resistance to prolong the operation life of responsible parts.

]]> Effects of HFMI Treatment on the Boron-Alloyed Austenite Medium-Manganese Steel 140Mn6Cr3TiB Deposit: Enhanced Wear Resistance Induced by Heterogeneous Microstructure Bohdan Trembach Bohdan Mordyuk Michal Krbata Pavlo Openko Vadim Zakiev Vladyslav Shyvaniuk Tetyana Vladimirova Mykola Skoryk Oleksii Kolomiitsev Vadym Krykun Yuliia Musairova Olga Gyrka doi: 10.3390/jmmp10070231 Journal of Manufacturing and Materials Processing 2026-06-30 Journal of Manufacturing and Materials Processing 2026-06-30 10 7 Article 231 10.3390/jmmp10070231 https://www.mdpi.com/2504-4494/10/7/231 JMMP, Vol. 10, Pages 230: Influence of Heat Input and Strength Matching on the Microstructure and Mechanical Properties of GMAW Butt-Welded S700MC High-Strength Low-Alloy Steel https://www.mdpi.com/2504-4494/10/7/230 High-strength low-alloy (HSLA) steels produced by thermomechanical controlled processing (TMCP) are widely used in structural applications because of their high strength and weldability. However, the performance of welded joints is strongly affected by welding thermal cycles. This study investigated the effects of heat input (0.6, 1.4, and 1.8 kJ/mm) and filler metal strength (matching and undermatching) on the microstructure and mechanical properties of S700MC steel joints produced by metal-cored arc welding (MCAW). Microstructural characterization, hardness measurements, tensile testing, Charpy impact testing, and analysis of variance (ANOVA) were performed. Heat input was identified as the dominant factor controlling heat-affected zone (HAZ) development and mechanical performance. Increasing heat input enlarged the HAZ and reduced hardness through enhanced microstructural recovery. Filler metal strength mainly influenced failure location and joint strength. The lowest heat input (0.6 kJ/mm) provided the highest strength retention, particularly with the matching consumable, but also produced localized hardness peaks approaching 400 HV0.01 at the weld metal (WM)/HAZ interface, reducing ductility and impact toughness. An intermediate heat input (1.4 kJ/mm) produced the best balance between strength and toughness by promoting a more homogeneous microstructure and smoother hardness distribution. These results provide practical guidance for optimizing welding procedures for TMCP HSLA steels. 2026-06-30 JMMP, Vol. 10, Pages 230: Influence of Heat Input and Strength Matching on the Microstructure and Mechanical Properties of GMAW Butt-Welded S700MC High-Strength Low-Alloy Steel

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070230

Authors: João Ricardo Boff Preichardt Rafael Luciano Dalcin Richard Thomas Lermen Ivan Guerra Machado

High-strength low-alloy (HSLA) steels produced by thermomechanical controlled processing (TMCP) are widely used in structural applications because of their high strength and weldability. However, the performance of welded joints is strongly affected by welding thermal cycles. This study investigated the effects of heat input (0.6, 1.4, and 1.8 kJ/mm) and filler metal strength (matching and undermatching) on the microstructure and mechanical properties of S700MC steel joints produced by metal-cored arc welding (MCAW). Microstructural characterization, hardness measurements, tensile testing, Charpy impact testing, and analysis of variance (ANOVA) were performed. Heat input was identified as the dominant factor controlling heat-affected zone (HAZ) development and mechanical performance. Increasing heat input enlarged the HAZ and reduced hardness through enhanced microstructural recovery. Filler metal strength mainly influenced failure location and joint strength. The lowest heat input (0.6 kJ/mm) provided the highest strength retention, particularly with the matching consumable, but also produced localized hardness peaks approaching 400 HV0.01 at the weld metal (WM)/HAZ interface, reducing ductility and impact toughness. An intermediate heat input (1.4 kJ/mm) produced the best balance between strength and toughness by promoting a more homogeneous microstructure and smoother hardness distribution. These results provide practical guidance for optimizing welding procedures for TMCP HSLA steels.

]]> Influence of Heat Input and Strength Matching on the Microstructure and Mechanical Properties of GMAW Butt-Welded S700MC High-Strength Low-Alloy Steel João Ricardo Boff Preichardt Rafael Luciano Dalcin Richard Thomas Lermen Ivan Guerra Machado doi: 10.3390/jmmp10070230 Journal of Manufacturing and Materials Processing 2026-06-30 Journal of Manufacturing and Materials Processing 2026-06-30 10 7 Article 230 10.3390/jmmp10070230 https://www.mdpi.com/2504-4494/10/7/230 JMMP, Vol. 10, Pages 229: Practical Multivariate Equivalency Testing for Additively Manufactured Parts: Comparing Independent and Dependent Cases https://www.mdpi.com/2504-4494/10/7/229 Additive manufacturing (AM) requalification and change-control workflows often require evidence that a candidate machine, parameter set, scanner subsystem, facility, or measurement workflow remains comparable to a stable reference process after a change, but fabrication and testing costs limit exhaustive multifeature studies. The aim of this study was to address this engineering design problem by developing a practical multifeature equivalency screening framework for AM settings in which prior engineering evidence already suggests that the candidate process should be comparable to the reference process. Building on prior work focused on the univariate problem, the proposed framework uses reference-defined percentile bins, feature-wise distributional tests, and family-wise error-rate control to screen for evidence of non-equivalency across multiple measured attributes. A direct joint-binning approach was first shown to become sample-intensive as dimensionality increases, after which an independent feature-wise method and an exploratory dependent bivariate extension were developed. Simulation-based power analyses quantified the trade-offs among power, detectable effect size, distributional resolution, feature count, and the combined costs of fabrication and measurement. In a laser-based powder bed fusion validation study with 40 observations per process and three corner-deviation features, the expected-equivalent AconityMIDI+ candidate satisfied all feature-wise equivalency criteria (V˜=0.207–0.214<CI+=0.276), whereas the expected non-equivalent SLM280 HL candidate failed all three feature-wise tests (V˜=0.357–1.000>CI+=0.276). These results support multivariate equivalency as a requalification screening tool for AM process comparability and change control, while confirming that it should not be interpreted as proof of physical-process identity or as a replacement for first-time formal qualification. Core procedures are implemented in the open-source R package MultivariateEquivalency. 2026-06-30 JMMP, Vol. 10, Pages 229: Practical Multivariate Equivalency Testing for Additively Manufactured Parts: Comparing Independent and Dependent Cases

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070229

Authors: Colin M. Lynch Rene Villalobos Brenda Leticia Valadez Mesta Cesar Gomez Guillen Jorge Mireles Ryan B. Wicker

Additive manufacturing (AM) requalification and change-control workflows often require evidence that a candidate machine, parameter set, scanner subsystem, facility, or measurement workflow remains comparable to a stable reference process after a change, but fabrication and testing costs limit exhaustive multifeature studies. The aim of this study was to address this engineering design problem by developing a practical multifeature equivalency screening framework for AM settings in which prior engineering evidence already suggests that the candidate process should be comparable to the reference process. Building on prior work focused on the univariate problem, the proposed framework uses reference-defined percentile bins, feature-wise distributional tests, and family-wise error-rate control to screen for evidence of non-equivalency across multiple measured attributes. A direct joint-binning approach was first shown to become sample-intensive as dimensionality increases, after which an independent feature-wise method and an exploratory dependent bivariate extension were developed. Simulation-based power analyses quantified the trade-offs among power, detectable effect size, distributional resolution, feature count, and the combined costs of fabrication and measurement. In a laser-based powder bed fusion validation study with 40 observations per process and three corner-deviation features, the expected-equivalent AconityMIDI+ candidate satisfied all feature-wise equivalency criteria (V˜=0.207–0.214<CI+=0.276), whereas the expected non-equivalent SLM280 HL candidate failed all three feature-wise tests (V˜=0.357–1.000>CI+=0.276). These results support multivariate equivalency as a requalification screening tool for AM process comparability and change control, while confirming that it should not be interpreted as proof of physical-process identity or as a replacement for first-time formal qualification. Core procedures are implemented in the open-source R package MultivariateEquivalency.

]]> Practical Multivariate Equivalency Testing for Additively Manufactured Parts: Comparing Independent and Dependent Cases Colin M. Lynch Rene Villalobos Brenda Leticia Valadez Mesta Cesar Gomez Guillen Jorge Mireles Ryan B. Wicker doi: 10.3390/jmmp10070229 Journal of Manufacturing and Materials Processing 2026-06-30 Journal of Manufacturing and Materials Processing 2026-06-30 10 7 Article 229 10.3390/jmmp10070229 https://www.mdpi.com/2504-4494/10/7/229 JMMP, Vol. 10, Pages 228: Mechanical Behaviour of Tube Fit Joints in EV Battery Systems: The Role of Material Selection https://www.mdpi.com/2504-4494/10/7/228 Tube-fit joining is a promising heat-free solution for busbar-to-prismatic cell terminal interconnections, offering rapid disassembly for repair, reuse, and recycling. This study experimentally investigates the mechanical behaviour of tube-fit joints under pull-out and shear loading, considering different joining forces and busbar–terminal material combinations. Increasing the joining force from 10 to 16 kN enhanced connector deformation and mechanical interlocking, resulting in a pronounced improvement in pull-out performance but only a limited change in shear capacity. A joining force of 13 kN provided the most suitable balance between mechanical performance and damage-free disassembly. Under pull-out loading, the response was primarily governed by the busbar material: copper busbars produced higher peak loads and larger displacements, whereas aluminium busbars exhibited stiffer responses and shorter pull-out strokes. Under shear loading, the different material combinations showed comparable peak loads and a predominantly connector-driven failure mechanism, indicating that shear capacity was mainly controlled by the connector. Increasing the aluminium busbar thickness enhanced joint stiffness and shear load capacity without changing the governing failure mechanism. Overall, this work provides new insights into the interplay between material selection and process parameters in tube fit joining, offering valuable guidance for the design of robust, disassemblable interconnections in next-generation EV battery systems. 2026-06-30 JMMP, Vol. 10, Pages 228: Mechanical Behaviour of Tube Fit Joints in EV Battery Systems: The Role of Material Selection

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070228

Authors: Vasco P. Henriques Mohammad Mehdi Kasaei Ricardo J. C. Carbas Eduardo A. S. Marques Lucas F. M. da Silva

Tube-fit joining is a promising heat-free solution for busbar-to-prismatic cell terminal interconnections, offering rapid disassembly for repair, reuse, and recycling. This study experimentally investigates the mechanical behaviour of tube-fit joints under pull-out and shear loading, considering different joining forces and busbar–terminal material combinations. Increasing the joining force from 10 to 16 kN enhanced connector deformation and mechanical interlocking, resulting in a pronounced improvement in pull-out performance but only a limited change in shear capacity. A joining force of 13 kN provided the most suitable balance between mechanical performance and damage-free disassembly. Under pull-out loading, the response was primarily governed by the busbar material: copper busbars produced higher peak loads and larger displacements, whereas aluminium busbars exhibited stiffer responses and shorter pull-out strokes. Under shear loading, the different material combinations showed comparable peak loads and a predominantly connector-driven failure mechanism, indicating that shear capacity was mainly controlled by the connector. Increasing the aluminium busbar thickness enhanced joint stiffness and shear load capacity without changing the governing failure mechanism. Overall, this work provides new insights into the interplay between material selection and process parameters in tube fit joining, offering valuable guidance for the design of robust, disassemblable interconnections in next-generation EV battery systems.

]]> Mechanical Behaviour of Tube Fit Joints in EV Battery Systems: The Role of Material Selection Vasco P. Henriques Mohammad Mehdi Kasaei Ricardo J. C. Carbas Eduardo A. S. Marques Lucas F. M. da Silva doi: 10.3390/jmmp10070228 Journal of Manufacturing and Materials Processing 2026-06-30 Journal of Manufacturing and Materials Processing 2026-06-30 10 7 Article 228 10.3390/jmmp10070228 https://www.mdpi.com/2504-4494/10/7/228 JMMP, Vol. 10, Pages 227: Development and Research of Electric Pulse Force Intensification Technology to Improve the Reliability and Cyclic Durability of Materials https://www.mdpi.com/2504-4494/10/7/227 Reduced service life of components, units, and assemblies operating under extreme conditions, characterized by high cyclically varying stresses, remains a significant issue. The present work addresses this problem by enhancing the reliability and cyclic durability of materials through electric pulse force intensification. As a result of the study, appropriate equipment for electric pulse force intensification was selected. A technology for electric pulse force intensification was developed, and process parameters such as current strength, current density, and pulse duration were optimized. Using statistical analysis of experimental data, 3D models were created, and empirical mathematical equations were derived to describe the influence of key process parameters on the cyclic durability of materials. The geometric parameters of cracks were examined during cyclic durability tests under bending with low-cycle loading, both before and after electric pulse activation. Using SEM, we studied the material structure in the crack region, revealing that pulsed electric current enhances cyclic life by “partial healing” of structural defects. Statistical modeling produced empirical equations expressing the relationships between various characteristics. The mechanism of defect partial healing in materials subjected to electric pulses was described, and the impact of electric pulse activation on samples was evaluated. This demonstrated the potential to fully restore a component’s service life after cyclic loading at 80% of its ultimate limit. 2026-06-30 JMMP, Vol. 10, Pages 227: Development and Research of Electric Pulse Force Intensification Technology to Improve the Reliability and Cyclic Durability of Materials

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070227

Authors: Peter Rusinov Alexey Pashkov Svetlana Tyurina Chao Zhang Andrey Merkulov Galina Dalskaya Zhanna Guminskaya Daria Gusevskaya George Kurapov Polina Sereda

Reduced service life of components, units, and assemblies operating under extreme conditions, characterized by high cyclically varying stresses, remains a significant issue. The present work addresses this problem by enhancing the reliability and cyclic durability of materials through electric pulse force intensification. As a result of the study, appropriate equipment for electric pulse force intensification was selected. A technology for electric pulse force intensification was developed, and process parameters such as current strength, current density, and pulse duration were optimized. Using statistical analysis of experimental data, 3D models were created, and empirical mathematical equations were derived to describe the influence of key process parameters on the cyclic durability of materials. The geometric parameters of cracks were examined during cyclic durability tests under bending with low-cycle loading, both before and after electric pulse activation. Using SEM, we studied the material structure in the crack region, revealing that pulsed electric current enhances cyclic life by “partial healing” of structural defects. Statistical modeling produced empirical equations expressing the relationships between various characteristics. The mechanism of defect partial healing in materials subjected to electric pulses was described, and the impact of electric pulse activation on samples was evaluated. This demonstrated the potential to fully restore a component’s service life after cyclic loading at 80% of its ultimate limit.

]]> Development and Research of Electric Pulse Force Intensification Technology to Improve the Reliability and Cyclic Durability of Materials Peter Rusinov Alexey Pashkov Svetlana Tyurina Chao Zhang Andrey Merkulov Galina Dalskaya Zhanna Guminskaya Daria Gusevskaya George Kurapov Polina Sereda doi: 10.3390/jmmp10070227 Journal of Manufacturing and Materials Processing 2026-06-30 Journal of Manufacturing and Materials Processing 2026-06-30 10 7 Article 227 10.3390/jmmp10070227 https://www.mdpi.com/2504-4494/10/7/227 JMMP, Vol. 10, Pages 225: A Review of Internal Structures in Additively Manufactured Turbomachinery Blades: Classification and Effects on Key Blade Characteristics https://www.mdpi.com/2504-4494/10/7/225 Additive manufacturing has become an important technology for turbomachinery blades because it enables lightweight components of high geometric complexity and allows the external shell and internal infill to be designed separately. However, published studies on blade internal structures remain fragmented because different works consider different cell types, materials, optimization formulations, and evaluation criteria, which complicates cross-study comparison. This review synthesizes 47 sources and classifies internal structures according to the method of geometric definition, distinguishing 2D parametric structures (class A1), 3D parametric strut-based and TPMS-based structures (class A2), free-topology structures obtained by topology optimization or generative design (class B), and hybrid structures combining parametric infill with free topology (class AB). Comparative analysis based on normalized data extracted from 17 studies is used to examine the effects of these structure classes on natural frequencies, stress state, thermal state, and fatigue life. The review is complemented by a structured study-by-study summary, which systematizes the studies used in the review discussion in terms of component type, material, additive-manufacturing process, internal-structure class, analysis method, investigated indicators, main results, and limitations. The available evidence indicates that class A1 structures are used mainly for mass reduction in narrow internal cavities, class B structures are especially effective for targeted material redistribution and often provide the largest increase in lower natural frequencies, whereas TPMS-based structures appear particularly promising for thermal-state-related applications. At the same time, fatigue life and manufacturing accuracy remain among the least studied and least experimentally validated characteristics. 2026-06-29 JMMP, Vol. 10, Pages 225: A Review of Internal Structures in Additively Manufactured Turbomachinery Blades: Classification and Effects on Key Blade Characteristics

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070225

Authors: Igor Melikhov Leonid Plotnikov Viacheslav Sedunin

Additive manufacturing has become an important technology for turbomachinery blades because it enables lightweight components of high geometric complexity and allows the external shell and internal infill to be designed separately. However, published studies on blade internal structures remain fragmented because different works consider different cell types, materials, optimization formulations, and evaluation criteria, which complicates cross-study comparison. This review synthesizes 47 sources and classifies internal structures according to the method of geometric definition, distinguishing 2D parametric structures (class A1), 3D parametric strut-based and TPMS-based structures (class A2), free-topology structures obtained by topology optimization or generative design (class B), and hybrid structures combining parametric infill with free topology (class AB). Comparative analysis based on normalized data extracted from 17 studies is used to examine the effects of these structure classes on natural frequencies, stress state, thermal state, and fatigue life. The review is complemented by a structured study-by-study summary, which systematizes the studies used in the review discussion in terms of component type, material, additive-manufacturing process, internal-structure class, analysis method, investigated indicators, main results, and limitations. The available evidence indicates that class A1 structures are used mainly for mass reduction in narrow internal cavities, class B structures are especially effective for targeted material redistribution and often provide the largest increase in lower natural frequencies, whereas TPMS-based structures appear particularly promising for thermal-state-related applications. At the same time, fatigue life and manufacturing accuracy remain among the least studied and least experimentally validated characteristics.

]]> A Review of Internal Structures in Additively Manufactured Turbomachinery Blades: Classification and Effects on Key Blade Characteristics Igor Melikhov Leonid Plotnikov Viacheslav Sedunin doi: 10.3390/jmmp10070225 Journal of Manufacturing and Materials Processing 2026-06-29 Journal of Manufacturing and Materials Processing 2026-06-29 10 7 Review 225 10.3390/jmmp10070225 https://www.mdpi.com/2504-4494/10/7/225 JMMP, Vol. 10, Pages 226: Experimental Determination of the Forming Limits of Steel Thin-Walled Tubes https://www.mdpi.com/2504-4494/10/7/226 This study presents an integrated experimental methodology to determine the forming and fracture limits of welded thin-walled steel tubes, with emphasis on weld-line effects and manufacturing-induced anisotropy. The methodology combines longitudinal and transverse uniaxial tensile tests, using specimens extracted from different positions relative to the weld line, with elastomer-based tube expansion tests. Digital Image Correlation, combined with time-dependent strain analysis, was used to identify the onset of localized necking, while local strain and thickness measurements near the fracture regions supported the determination of fracture limits. This experimental work covered strain paths in the principal strain space ranging from uniaxial tension to near plane-strain expansion within the investigated conditions, enabling the experimental determination of both the Forming Limit Curve and the Fracture Forming Line for the welded tube material. Results reveal a pronounced directional dependence of mechanical response and formability. Transverse specimens exhibited higher yield and ultimate tensile strengths but lower ductility, whereas longitudinal specimens showed greater elongation and strain-hardening capacity. Strain localization and fracture were governed by the combined effects of local thickness variations, weld heterogeneity, and manufacturing-induced anisotropy. In longitudinal specimens, fracture occurred preferentially along the weld line, while in transverse specimens it developed away from the weld region, indicating distinct failure mechanisms depending on the loading direction. These findings highlight the need to account for weld-related heterogeneity and manufacturing history when assessing the formability of welded thin-walled tubes. The proposed methodology provides valuable experimental data for improving failure prediction and supporting the design, simulation, and optimization of welded tubular components. 2026-06-29 JMMP, Vol. 10, Pages 226: Experimental Determination of the Forming Limits of Steel Thin-Walled Tubes

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070226

Authors: João P. G. Magrinho Eneko Sáenz-De-Argandoña Joseba Mendiguren Maria Beatriz Silva

This study presents an integrated experimental methodology to determine the forming and fracture limits of welded thin-walled steel tubes, with emphasis on weld-line effects and manufacturing-induced anisotropy. The methodology combines longitudinal and transverse uniaxial tensile tests, using specimens extracted from different positions relative to the weld line, with elastomer-based tube expansion tests. Digital Image Correlation, combined with time-dependent strain analysis, was used to identify the onset of localized necking, while local strain and thickness measurements near the fracture regions supported the determination of fracture limits. This experimental work covered strain paths in the principal strain space ranging from uniaxial tension to near plane-strain expansion within the investigated conditions, enabling the experimental determination of both the Forming Limit Curve and the Fracture Forming Line for the welded tube material. Results reveal a pronounced directional dependence of mechanical response and formability. Transverse specimens exhibited higher yield and ultimate tensile strengths but lower ductility, whereas longitudinal specimens showed greater elongation and strain-hardening capacity. Strain localization and fracture were governed by the combined effects of local thickness variations, weld heterogeneity, and manufacturing-induced anisotropy. In longitudinal specimens, fracture occurred preferentially along the weld line, while in transverse specimens it developed away from the weld region, indicating distinct failure mechanisms depending on the loading direction. These findings highlight the need to account for weld-related heterogeneity and manufacturing history when assessing the formability of welded thin-walled tubes. The proposed methodology provides valuable experimental data for improving failure prediction and supporting the design, simulation, and optimization of welded tubular components.

]]> Experimental Determination of the Forming Limits of Steel Thin-Walled Tubes João P. G. Magrinho Eneko Sáenz-De-Argandoña Joseba Mendiguren Maria Beatriz Silva doi: 10.3390/jmmp10070226 Journal of Manufacturing and Materials Processing 2026-06-29 Journal of Manufacturing and Materials Processing 2026-06-29 10 7 Article 226 10.3390/jmmp10070226 https://www.mdpi.com/2504-4494/10/7/226 JMMP, Vol. 10, Pages 224: Sheep Wool Biochar-Enhanced HDPE Composites https://www.mdpi.com/2504-4494/10/7/224 Animal-based biomass is gaining increasing attention in composites technology as a sustainable alternative to conventional fillers, offering a green pathway in the generation of composites exhibiting improved performance via waste valorization. In the present study, carbonized sheep wool was incorporated into high-density polyethylene (HDPE) in various weight ratios up to 10% wt. to fabricate composite specimens. The resulting composites were evaluated through Dynamic Mechanical Analysis (DMA), while their morphology and chemical structure were investigated by Scanning Electron Microscopy (SEM) combined with Energy Dispersive X-ray Spectroscopy (SEM-EDS) and Fourier Transform Infrared Spectroscopy (FTIR), respectively. FTIR analysis revealed the presence of residual keratin-derived oxygen- and nitrogen-containing functional groups, indicating the retention of chemically active surface functionalities upon low-temperature carbonization. This evidence is further corroborated through qualitative (SEM-EDS) elemental mapping of the pristine surfaces of sheep wool fibers and the pyrolyzed biochar product. DMA experimental data demonstrated that sheep wool-derived biochar (SWB) can effectively reinforce HDPE, resulting in stiffness enhancement while reducing viscous dissipation, thereby highlighting its potential as a sustainable, eco-friendly filler and a viable pathway for circular valorization of animal biomass waste. 2026-06-29 JMMP, Vol. 10, Pages 224: Sheep Wool Biochar-Enhanced HDPE Composites

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070224

Authors: Viktoria Theodorou Ioannis Pashalidis Panagiotis S. Ioannou Theodora Krasia-Christoforou

Animal-based biomass is gaining increasing attention in composites technology as a sustainable alternative to conventional fillers, offering a green pathway in the generation of composites exhibiting improved performance via waste valorization. In the present study, carbonized sheep wool was incorporated into high-density polyethylene (HDPE) in various weight ratios up to 10% wt. to fabricate composite specimens. The resulting composites were evaluated through Dynamic Mechanical Analysis (DMA), while their morphology and chemical structure were investigated by Scanning Electron Microscopy (SEM) combined with Energy Dispersive X-ray Spectroscopy (SEM-EDS) and Fourier Transform Infrared Spectroscopy (FTIR), respectively. FTIR analysis revealed the presence of residual keratin-derived oxygen- and nitrogen-containing functional groups, indicating the retention of chemically active surface functionalities upon low-temperature carbonization. This evidence is further corroborated through qualitative (SEM-EDS) elemental mapping of the pristine surfaces of sheep wool fibers and the pyrolyzed biochar product. DMA experimental data demonstrated that sheep wool-derived biochar (SWB) can effectively reinforce HDPE, resulting in stiffness enhancement while reducing viscous dissipation, thereby highlighting its potential as a sustainable, eco-friendly filler and a viable pathway for circular valorization of animal biomass waste.

]]> Sheep Wool Biochar-Enhanced HDPE Composites Viktoria Theodorou Ioannis Pashalidis Panagiotis S. Ioannou Theodora Krasia-Christoforou doi: 10.3390/jmmp10070224 Journal of Manufacturing and Materials Processing 2026-06-29 Journal of Manufacturing and Materials Processing 2026-06-29 10 7 Article 224 10.3390/jmmp10070224 https://www.mdpi.com/2504-4494/10/7/224 JMMP, Vol. 10, Pages 223: Recent Advances and Challenges in Hybrid Additive Manufacturing: Classification, Architectures, and Industrial Applications https://www.mdpi.com/2504-4494/10/7/223 Hybrid additive manufacturing (HAM) integrates additive and subtractive processes within a unified production system, combining the geometric flexibility and material efficiency of additive manufacturing with the dimensional accuracy and surface quality of conventional machining. This review provides a comprehensive analysis of HAM technologies through a proposed four-criterion classification framework encompassing process integration strategy, additive manufacturing process type, machine architecture, and application domain. DED-based, PBF-based, and polymer-based hybrid systems are examined alongside integrated hybrid machines, retrofit solutions, and robotic architectures. A comparative analysis of representative commercial platforms evaluates build envelope, integration strategy, and monitoring capability. Documented performance outcomes across aerospace, automotive, energy, and biomedical sectors confirm substantial improvements in surface quality, fatigue performance, dimensional accuracy, and material efficiency relative to conventional manufacturing routes. Current limitations are critically assessed across technical, process integration, and economic dimensions, and a structured near-to-long-term research roadmap is proposed, prioritising in-process sensing and toolpath standardisation, digital twin-based adaptive process planning, and ultimately autonomous hybrid manufacturing cells with lifecycle certification. These findings position HAM as a central enabling technology for intelligent, flexible, and sustainable production within Industry 4.0 and Industry 5.0 paradigms. 2026-06-27 JMMP, Vol. 10, Pages 223: Recent Advances and Challenges in Hybrid Additive Manufacturing: Classification, Architectures, and Industrial Applications

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070223

Authors: Sheraly Bekbolatov Asset Rakishev Khairur Rijal Jamaludin

Hybrid additive manufacturing (HAM) integrates additive and subtractive processes within a unified production system, combining the geometric flexibility and material efficiency of additive manufacturing with the dimensional accuracy and surface quality of conventional machining. This review provides a comprehensive analysis of HAM technologies through a proposed four-criterion classification framework encompassing process integration strategy, additive manufacturing process type, machine architecture, and application domain. DED-based, PBF-based, and polymer-based hybrid systems are examined alongside integrated hybrid machines, retrofit solutions, and robotic architectures. A comparative analysis of representative commercial platforms evaluates build envelope, integration strategy, and monitoring capability. Documented performance outcomes across aerospace, automotive, energy, and biomedical sectors confirm substantial improvements in surface quality, fatigue performance, dimensional accuracy, and material efficiency relative to conventional manufacturing routes. Current limitations are critically assessed across technical, process integration, and economic dimensions, and a structured near-to-long-term research roadmap is proposed, prioritising in-process sensing and toolpath standardisation, digital twin-based adaptive process planning, and ultimately autonomous hybrid manufacturing cells with lifecycle certification. These findings position HAM as a central enabling technology for intelligent, flexible, and sustainable production within Industry 4.0 and Industry 5.0 paradigms.

]]> Recent Advances and Challenges in Hybrid Additive Manufacturing: Classification, Architectures, and Industrial Applications Sheraly Bekbolatov Asset Rakishev Khairur Rijal Jamaludin doi: 10.3390/jmmp10070223 Journal of Manufacturing and Materials Processing 2026-06-27 Journal of Manufacturing and Materials Processing 2026-06-27 10 7 Review 223 10.3390/jmmp10070223 https://www.mdpi.com/2504-4494/10/7/223 JMMP, Vol. 10, Pages 222: 3D FFF-Type Printer Upgrade for the Use of Viscous-Filled Polymeric Materials https://www.mdpi.com/2504-4494/10/7/222 Recently, there has been a significant expansion of additive technologies, especially Fused Filament Fabrication (FFF). This article aims to upgrade a commercial 3D printer to develop viscous polymeric materials, as this option is not currently available. The FFF method is primarily used with thermoplastics and elastomers in filament form. However, materials derived from various water-soluble acrylates offer significant potential, with advantages including environmental friendliness and desirable mechanical and visual properties. The possibility of using a viscous polymer as a carrier for metal material prior to sintering is also a significant factor. The aim of the text is to present the preparation of a 3D printer suitable for printing the above materials. The main requirement was to modify the selected printer with minimal interference with HW and SW. We mainly focused on adjusting the print head. A new prototype for the printing of viscous polymeric materials was visualized. Furthermore, the individual components were designed and printed; a functional system capable of processing these materials was assembled. 2026-06-27 JMMP, Vol. 10, Pages 222: 3D FFF-Type Printer Upgrade for the Use of Viscous-Filled Polymeric Materials

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070222

Authors: Karel Dvořák Jana Dvořáková Michal Bílek Lucie Zárybnická

Recently, there has been a significant expansion of additive technologies, especially Fused Filament Fabrication (FFF). This article aims to upgrade a commercial 3D printer to develop viscous polymeric materials, as this option is not currently available. The FFF method is primarily used with thermoplastics and elastomers in filament form. However, materials derived from various water-soluble acrylates offer significant potential, with advantages including environmental friendliness and desirable mechanical and visual properties. The possibility of using a viscous polymer as a carrier for metal material prior to sintering is also a significant factor. The aim of the text is to present the preparation of a 3D printer suitable for printing the above materials. The main requirement was to modify the selected printer with minimal interference with HW and SW. We mainly focused on adjusting the print head. A new prototype for the printing of viscous polymeric materials was visualized. Furthermore, the individual components were designed and printed; a functional system capable of processing these materials was assembled.

]]> 3D FFF-Type Printer Upgrade for the Use of Viscous-Filled Polymeric Materials Karel Dvořák Jana Dvořáková Michal Bílek Lucie Zárybnická doi: 10.3390/jmmp10070222 Journal of Manufacturing and Materials Processing 2026-06-27 Journal of Manufacturing and Materials Processing 2026-06-27 10 7 Article 222 10.3390/jmmp10070222 https://www.mdpi.com/2504-4494/10/7/222 JMMP, Vol. 10, Pages 220: Microstructural and Mechanical Characterization of a CMT-WAAM Fabricated 17-4PH Stainless Steel/Inconel 625 Bimetallic Structure https://www.mdpi.com/2504-4494/10/7/220 The demand for large-scale high-performance components with tailored properties in the aerospace and automotive industries has increased interest in multi-material additive manufacturing (AM). Among AM techniques, the Wire Arc Additive Manufacturing (WAAM) process is preferred for bimetallic fabrication due to high deposition rates, low equipment costs, and efficient material utilization. However, differences in metallurgical and thermal properties between dissimilar alloys can cause heat accumulation, leading to thermal stresses, cracking, and weak interfacial bonds. To the best of the authors’ knowledge, no study has reported the fabrication and characterization of a 17-4PH SS/Inconel 625 joint using the large-scale CMT-WAAM Process. To fill this gap, this study characterizes the microstructure and elemental distribution of the joint using scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray Microscopy (XRM) and energy dispersive spectroscopy (EDS). Microstructural analysis revealed a martensitic matrix with retained δ-ferrite in the 17-4PH region, a fully austenitic γ-phase in the Inconel 625 region, and a mixed BCC–FCC transition zone at the interface. EDS results demonstrated a Fe–Ni compositional gradient across the interface. Radiographic inspection confirmed a defect-free build, and XRM results showed a porosity of less than 0.003% only in the 17-4PH region. Tensile testing confirmed joint integrity, with fracture occurring in the Inconel 625 region, and average yield and ultimate tensile strengths of 391 ± 7 MPa and 676 ± 9 MPa, respectively. The simplified Johnson-Cook constitutive model successfully predicted the ultimate tensile strength (UTS), with a prediction error of 9.3% compared to the experimental result. Furthermore, a novel 3D-structured light scanner technique was developed and validated with an extensometer to provide insight into localized strain behavior. 2026-06-26 JMMP, Vol. 10, Pages 220: Microstructural and Mechanical Characterization of a CMT-WAAM Fabricated 17-4PH Stainless Steel/Inconel 625 Bimetallic Structure

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070220

Authors: Muhammad Irfan Mohammad Keshmiri Shalini Singh Abba Abubakar Sajid Ullah Butt Yun-Fei Fu Abul Fazal Arif Osezua Ibhadode Ahmed Jawad Qureshi

The demand for large-scale high-performance components with tailored properties in the aerospace and automotive industries has increased interest in multi-material additive manufacturing (AM). Among AM techniques, the Wire Arc Additive Manufacturing (WAAM) process is preferred for bimetallic fabrication due to high deposition rates, low equipment costs, and efficient material utilization. However, differences in metallurgical and thermal properties between dissimilar alloys can cause heat accumulation, leading to thermal stresses, cracking, and weak interfacial bonds. To the best of the authors’ knowledge, no study has reported the fabrication and characterization of a 17-4PH SS/Inconel 625 joint using the large-scale CMT-WAAM Process. To fill this gap, this study characterizes the microstructure and elemental distribution of the joint using scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray Microscopy (XRM) and energy dispersive spectroscopy (EDS). Microstructural analysis revealed a martensitic matrix with retained δ-ferrite in the 17-4PH region, a fully austenitic γ-phase in the Inconel 625 region, and a mixed BCC–FCC transition zone at the interface. EDS results demonstrated a Fe–Ni compositional gradient across the interface. Radiographic inspection confirmed a defect-free build, and XRM results showed a porosity of less than 0.003% only in the 17-4PH region. Tensile testing confirmed joint integrity, with fracture occurring in the Inconel 625 region, and average yield and ultimate tensile strengths of 391 ± 7 MPa and 676 ± 9 MPa, respectively. The simplified Johnson-Cook constitutive model successfully predicted the ultimate tensile strength (UTS), with a prediction error of 9.3% compared to the experimental result. Furthermore, a novel 3D-structured light scanner technique was developed and validated with an extensometer to provide insight into localized strain behavior.

]]> Microstructural and Mechanical Characterization of a CMT-WAAM Fabricated 17-4PH Stainless Steel/Inconel 625 Bimetallic Structure Muhammad Irfan Mohammad Keshmiri Shalini Singh Abba Abubakar Sajid Ullah Butt Yun-Fei Fu Abul Fazal Arif Osezua Ibhadode Ahmed Jawad Qureshi doi: 10.3390/jmmp10070220 Journal of Manufacturing and Materials Processing 2026-06-26 Journal of Manufacturing and Materials Processing 2026-06-26 10 7 Article 220 10.3390/jmmp10070220 https://www.mdpi.com/2504-4494/10/7/220 JMMP, Vol. 10, Pages 221: Analysis of Profile and Surface Roughness of Holes Drilled in Basalt Fiber Reinforced Polymers Laminates: Statistical Analysis and Predictive Approach Based on Machine Learning https://www.mdpi.com/2504-4494/10/7/221 Fiber-reinforced polymers such as basalt fiber-reinforced polymers (BFRP) can be used in structural parts, which often require assembly operations. Thus, the surface quality after drilling operations is especially important. BFRP laminates have been drilled with three different tools, and their profile roughness and surface roughness have been evaluated by analyzing the following variables: average roughness (Ra), maximum height of profile (Rz), arithmetic mean height (Sa) and maximum height (Sz), by means of an optical system. The optical measurement of surface roughness has been hampered by fiber breakage. A statistical analysis has allowed for developing a general linear model that predicts the values of variables. The fitted model for Ra and Rz has a variation coefficient of 97.00% and 95.58% respectively, while that 91.74% and 68.02% for Sa at the inlet hole and outlet hole respectively; and 86.08% and 82.22% for Sz at the inlet hole and outlet hole respectively. Additionally, different machine learning regression algorithms have been applied using different configurations to establish prediction models of the main rugosity parameters. In this way, linear methods, Gaussian regression methods, Support Vector Machines, and fine trees have been applied using the rotation speed, feed rates, and tool as features. Also, a neural network has been optimized and applied for the same goal. The methods yielded satisfactory prediction results within the tested experimental domain for some roughness parameters. Although the behavior of all variables is similar across all drill bit types, drill bits with a point angle of 120° provided better results. 2026-06-26 JMMP, Vol. 10, Pages 221: Analysis of Profile and Surface Roughness of Holes Drilled in Basalt Fiber Reinforced Polymers Laminates: Statistical Analysis and Predictive Approach Based on Machine Learning

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070221

Authors: Jorge Ayllón Manuel Rodríguez-Martín Rosario Domingo

Fiber-reinforced polymers such as basalt fiber-reinforced polymers (BFRP) can be used in structural parts, which often require assembly operations. Thus, the surface quality after drilling operations is especially important. BFRP laminates have been drilled with three different tools, and their profile roughness and surface roughness have been evaluated by analyzing the following variables: average roughness (Ra), maximum height of profile (Rz), arithmetic mean height (Sa) and maximum height (Sz), by means of an optical system. The optical measurement of surface roughness has been hampered by fiber breakage. A statistical analysis has allowed for developing a general linear model that predicts the values of variables. The fitted model for Ra and Rz has a variation coefficient of 97.00% and 95.58% respectively, while that 91.74% and 68.02% for Sa at the inlet hole and outlet hole respectively; and 86.08% and 82.22% for Sz at the inlet hole and outlet hole respectively. Additionally, different machine learning regression algorithms have been applied using different configurations to establish prediction models of the main rugosity parameters. In this way, linear methods, Gaussian regression methods, Support Vector Machines, and fine trees have been applied using the rotation speed, feed rates, and tool as features. Also, a neural network has been optimized and applied for the same goal. The methods yielded satisfactory prediction results within the tested experimental domain for some roughness parameters. Although the behavior of all variables is similar across all drill bit types, drill bits with a point angle of 120° provided better results.

]]> Analysis of Profile and Surface Roughness of Holes Drilled in Basalt Fiber Reinforced Polymers Laminates: Statistical Analysis and Predictive Approach Based on Machine Learning Jorge Ayllón Manuel Rodríguez-Martín Rosario Domingo doi: 10.3390/jmmp10070221 Journal of Manufacturing and Materials Processing 2026-06-26 Journal of Manufacturing and Materials Processing 2026-06-26 10 7 Article 221 10.3390/jmmp10070221 https://www.mdpi.com/2504-4494/10/7/221 JMMP, Vol. 10, Pages 219: Neural Network Enabled Process Parameter Optimization for Laser Powder Bed Fusion of Inconel 718 https://www.mdpi.com/2504-4494/10/7/219 Laser powder bed fusion (LPBF) is a widely utilized metal additive manufacturing (AM) process for fabricating intricate geometries with high mechanical strength. However, achieving defect-free parts remains challenging due to complex thermodynamics and process variability. Component quality is primarily determined by mel-pool morphology, which depends on key process parameters such as laser power, scan speed, and layer thickness. Improper parameter selection causes defects like porosity (keyhole and lack of fusion), balling, and residual stresses, compromising structural integrity. Optimizing these parameters is crucial but difficult due to the multi-scale, multi-physics nature of the process, which traditionally relies on costly, time-intensive experimental trials. We present results from a data-driven approach using machine learning (ML) models to predict and optimize LPBF melt-pool characteristics, reducing reliance on trial-and-error experimentation. We find that laser power and scan speed predominantly influence the melt-pool formation. Higher scan speeds produce more favorable melt pools, whereas excessive laser power at low scan speeds leads to deep keyhole defects. To predict and classify melt pools efficiently, several ML models are deployed, including logistic regression, decision trees, ensemble learning, and fully connected neural networks. The standard neural network achieved the highest cross-validated macro-F1 score of 0.978 ± 0.014, while the weighted neural network achieved the highest recall for the rare optimal melt-pool class, 0.967 ± 0.050. These findings show that class-weighted learning provides a recall-oriented strategy for identifying suitable LPBF process windows, while avoiding overreliance on single train-test split performance. The findings underscore the effectiveness of ML in accurately classifying LPBF melt pools to rapidly identify optimal process parameters. 2026-06-26 JMMP, Vol. 10, Pages 219: Neural Network Enabled Process Parameter Optimization for Laser Powder Bed Fusion of Inconel 718

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070219

Authors: Debajyoti Adak Mohammad Basit Akram Somnath Roy Ganesh Balasubramanian

Laser powder bed fusion (LPBF) is a widely utilized metal additive manufacturing (AM) process for fabricating intricate geometries with high mechanical strength. However, achieving defect-free parts remains challenging due to complex thermodynamics and process variability. Component quality is primarily determined by mel-pool morphology, which depends on key process parameters such as laser power, scan speed, and layer thickness. Improper parameter selection causes defects like porosity (keyhole and lack of fusion), balling, and residual stresses, compromising structural integrity. Optimizing these parameters is crucial but difficult due to the multi-scale, multi-physics nature of the process, which traditionally relies on costly, time-intensive experimental trials. We present results from a data-driven approach using machine learning (ML) models to predict and optimize LPBF melt-pool characteristics, reducing reliance on trial-and-error experimentation. We find that laser power and scan speed predominantly influence the melt-pool formation. Higher scan speeds produce more favorable melt pools, whereas excessive laser power at low scan speeds leads to deep keyhole defects. To predict and classify melt pools efficiently, several ML models are deployed, including logistic regression, decision trees, ensemble learning, and fully connected neural networks. The standard neural network achieved the highest cross-validated macro-F1 score of 0.978 ± 0.014, while the weighted neural network achieved the highest recall for the rare optimal melt-pool class, 0.967 ± 0.050. These findings show that class-weighted learning provides a recall-oriented strategy for identifying suitable LPBF process windows, while avoiding overreliance on single train-test split performance. The findings underscore the effectiveness of ML in accurately classifying LPBF melt pools to rapidly identify optimal process parameters.

]]> Neural Network Enabled Process Parameter Optimization for Laser Powder Bed Fusion of Inconel 718 Debajyoti Adak Mohammad Basit Akram Somnath Roy Ganesh Balasubramanian doi: 10.3390/jmmp10070219 Journal of Manufacturing and Materials Processing 2026-06-26 Journal of Manufacturing and Materials Processing 2026-06-26 10 7 Article 219 10.3390/jmmp10070219 https://www.mdpi.com/2504-4494/10/7/219 JMMP, Vol. 10, Pages 218: Research on Protection Efficiency of Bottom Guard Plate of Lithium-Ion Power Batteries Under Ball Impact Working Conditions https://www.mdpi.com/2504-4494/10/7/218 To address safety issues caused by the bottom impact of the power battery in new energy vehicles, a lightweight bottom panel design scheme based on long glass fiber-reinforced polypropylene (LGF/PP) honeycomb composite was proposed. By employing the sandwich structure with an LGF/PP surface material/polypropylene honeycomb core combined with high-shear-strength structural adhesive bonding technology, ball impact protection for the power battery bottom is greatly improved. A ball striking test was carried out in accordance with the requirements and test methods of bottom anti-collision for pure electric passenger vehicles (T/CSAE 244-2021), and the performance differences of traditional steel bottom guards were compared. The results show that the optimized honeycomb composite bottom guard plate (surface thickness 1.3 mm/honeycomb core 8 mm) is able to reduce the deformation of the aluminum plate to 10.4 mm, resulting in deformation that is only 68% of that observed with the steel bottom guard plate while achieving a 43% reduction in weight. The deformation of the aluminum plate was further reduced to 42.3% with the introduction of a structural adhesive with a 5 MPa shear strength. In addition, the honeycomb structure exhibits controllable plastic deformation after impact, while the steel bottom guard plate is severely distorted but not ruptured, highlighting the damage tolerance and energy absorption advantages of the composite material design. The honeycomb composite bottom guard plate outperforms the traditional scheme in terms of light weight, protection performance and cost. This work contributes to the field of power battery bottom protection. 2026-06-26 JMMP, Vol. 10, Pages 218: Research on Protection Efficiency of Bottom Guard Plate of Lithium-Ion Power Batteries Under Ball Impact Working Conditions

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070218

Authors: Yong Zeng Hongguang Huang Jie Hu Tegoeh Tjahjowidodo Ming Wu

To address safety issues caused by the bottom impact of the power battery in new energy vehicles, a lightweight bottom panel design scheme based on long glass fiber-reinforced polypropylene (LGF/PP) honeycomb composite was proposed. By employing the sandwich structure with an LGF/PP surface material/polypropylene honeycomb core combined with high-shear-strength structural adhesive bonding technology, ball impact protection for the power battery bottom is greatly improved. A ball striking test was carried out in accordance with the requirements and test methods of bottom anti-collision for pure electric passenger vehicles (T/CSAE 244-2021), and the performance differences of traditional steel bottom guards were compared. The results show that the optimized honeycomb composite bottom guard plate (surface thickness 1.3 mm/honeycomb core 8 mm) is able to reduce the deformation of the aluminum plate to 10.4 mm, resulting in deformation that is only 68% of that observed with the steel bottom guard plate while achieving a 43% reduction in weight. The deformation of the aluminum plate was further reduced to 42.3% with the introduction of a structural adhesive with a 5 MPa shear strength. In addition, the honeycomb structure exhibits controllable plastic deformation after impact, while the steel bottom guard plate is severely distorted but not ruptured, highlighting the damage tolerance and energy absorption advantages of the composite material design. The honeycomb composite bottom guard plate outperforms the traditional scheme in terms of light weight, protection performance and cost. This work contributes to the field of power battery bottom protection.

]]> Research on Protection Efficiency of Bottom Guard Plate of Lithium-Ion Power Batteries Under Ball Impact Working Conditions Yong Zeng Hongguang Huang Jie Hu Tegoeh Tjahjowidodo Ming Wu doi: 10.3390/jmmp10070218 Journal of Manufacturing and Materials Processing 2026-06-26 Journal of Manufacturing and Materials Processing 2026-06-26 10 7 Article 218 10.3390/jmmp10070218 https://www.mdpi.com/2504-4494/10/7/218 JMMP, Vol. 10, Pages 217: Recent Advances and Future Perspectives in Friction Stir Welding and Processing: A Review https://www.mdpi.com/2504-4494/10/7/217 Friction stir welding (FSW) began as a fairly specialized joining method, but over the past three decades it has evolved into something considerably more versatile, a manufacturing platform that now handles complex multi-material assemblies and solid-state additive processes with reasonable reliability. This review follows this evolution, paying particular attention to friction stir additive manufacturing (FSAM) and the persistent difficulties that arise when joining dissimilar systems, such as aluminum to steel or metals to polymers, where the fate of the joint is largely decided by how well the intermetallic compounds are kept under control. Machine learning, artificial intelligence, and high-fidelity numerical models are reducing the reliance on trial-and-error that once dominated parameter selection and defect prediction, bringing FSW closer to the operating principles of Industry 4.0. Hybrid variants, including ultrasonically assisted and underwater FSW, also receive attention here, as they offer researchers finer control over heat generation and plastic flow than the standard process allows. Throughout the study, microstructural observations are directly connected to mechanical results, with the aim of analyzing the current state of solid-state manufacturing and identifying the questions that most urgently need answering. 2026-06-25 JMMP, Vol. 10, Pages 217: Recent Advances and Future Perspectives in Friction Stir Welding and Processing: A Review

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070217

Authors: Dan Cătălin Bîrsan Florin Susac

Friction stir welding (FSW) began as a fairly specialized joining method, but over the past three decades it has evolved into something considerably more versatile, a manufacturing platform that now handles complex multi-material assemblies and solid-state additive processes with reasonable reliability. This review follows this evolution, paying particular attention to friction stir additive manufacturing (FSAM) and the persistent difficulties that arise when joining dissimilar systems, such as aluminum to steel or metals to polymers, where the fate of the joint is largely decided by how well the intermetallic compounds are kept under control. Machine learning, artificial intelligence, and high-fidelity numerical models are reducing the reliance on trial-and-error that once dominated parameter selection and defect prediction, bringing FSW closer to the operating principles of Industry 4.0. Hybrid variants, including ultrasonically assisted and underwater FSW, also receive attention here, as they offer researchers finer control over heat generation and plastic flow than the standard process allows. Throughout the study, microstructural observations are directly connected to mechanical results, with the aim of analyzing the current state of solid-state manufacturing and identifying the questions that most urgently need answering.

]]> Recent Advances and Future Perspectives in Friction Stir Welding and Processing: A Review Dan Cătălin Bîrsan Florin Susac doi: 10.3390/jmmp10070217 Journal of Manufacturing and Materials Processing 2026-06-25 Journal of Manufacturing and Materials Processing 2026-06-25 10 7 Review 217 10.3390/jmmp10070217 https://www.mdpi.com/2504-4494/10/7/217 JMMP, Vol. 10, Pages 216: Numerical Investigation of Residual Stress Distribution in Double-Lap T-Joints Effects of Welding Sequence https://www.mdpi.com/2504-4494/10/7/216 This study investigates residual stress development in double-lap T-joints fabricated from medium- and heavy-gauge steel plates. A three-dimensional thermo-mechanically coupled finite element model was developed in Abaqus and validated against blind-hole drilling measurements. Four distinct welding sequence schemes were systematically implemented to quantify their influence on the spatial distribution, peak magnitudes, and evolution trajectories of individual residual stress components (σx, σγ, σz). Results demonstrate that the inherent structural rigidity of medium-to-thick plate assemblies strongly constrains global distortion but does not eliminate sensitivity to sequencing at the local stress level. Although equivalent residual stress peaks remain largely insensitive to welding sequence, the distributions of principal stress components exhibit pronounced sequence-dependent heterogeneity. Specifically, single-side continuous unidirectional welding leverages interpass residual heat accumulation to suppress longitudinal tensile stress, achieving a peak value of 449.9 MPa, the lowest among all configurations. In contrast, double-sided alternating reverse welding promotes thermal dispersion across the joint, thereby reducing both transverse tensile stress magnitude and stress concentration in the distal heat-affected zone. Collectively, these findings establish that optimizing welding sequences for double-lap T-joints in medium-to-heavy plates centers not on minimizing global equivalent stress, but on deliberately tailoring the spatial partitioning and balance of individual stress components, a principle that directly informs robust, performance-driven weld path selection in structural fabrication. 2026-06-25 JMMP, Vol. 10, Pages 216: Numerical Investigation of Residual Stress Distribution in Double-Lap T-Joints Effects of Welding Sequence

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070216

Authors: Kuangang Fan Kai Ling Shun Ye Lirong Huang Changlai Sun Yangwen Gong

This study investigates residual stress development in double-lap T-joints fabricated from medium- and heavy-gauge steel plates. A three-dimensional thermo-mechanically coupled finite element model was developed in Abaqus and validated against blind-hole drilling measurements. Four distinct welding sequence schemes were systematically implemented to quantify their influence on the spatial distribution, peak magnitudes, and evolution trajectories of individual residual stress components (σx, σγ, σz). Results demonstrate that the inherent structural rigidity of medium-to-thick plate assemblies strongly constrains global distortion but does not eliminate sensitivity to sequencing at the local stress level. Although equivalent residual stress peaks remain largely insensitive to welding sequence, the distributions of principal stress components exhibit pronounced sequence-dependent heterogeneity. Specifically, single-side continuous unidirectional welding leverages interpass residual heat accumulation to suppress longitudinal tensile stress, achieving a peak value of 449.9 MPa, the lowest among all configurations. In contrast, double-sided alternating reverse welding promotes thermal dispersion across the joint, thereby reducing both transverse tensile stress magnitude and stress concentration in the distal heat-affected zone. Collectively, these findings establish that optimizing welding sequences for double-lap T-joints in medium-to-heavy plates centers not on minimizing global equivalent stress, but on deliberately tailoring the spatial partitioning and balance of individual stress components, a principle that directly informs robust, performance-driven weld path selection in structural fabrication.

]]> Numerical Investigation of Residual Stress Distribution in Double-Lap T-Joints Effects of Welding Sequence Kuangang Fan Kai Ling Shun Ye Lirong Huang Changlai Sun Yangwen Gong doi: 10.3390/jmmp10070216 Journal of Manufacturing and Materials Processing 2026-06-25 Journal of Manufacturing and Materials Processing 2026-06-25 10 7 Article 216 10.3390/jmmp10070216 https://www.mdpi.com/2504-4494/10/7/216 JMMP, Vol. 10, Pages 215: Sample Partitioning for Uncertainty Reduction in FEA-Based Milling Stability Prediction https://www.mdpi.com/2504-4494/10/7/215 Milling stability prediction requires tool and workpiece dynamics and cutting force coefficients, and uncertainty in these inputs propagates to the predicted stability maps. This study experimentally evaluates sample partitioning for uncertainty reduction in milling stability when the workpiece dynamics are predicted using finite element analysis (FEA). The FEA-predicted workpiece natural frequency and modal stiffness differed from the tap-tested reference values by 4.9% and 14.3%, respectively, leading to different predicted stability maps. Initial candidate stability maps were generated by Monte Carlo simulation using the uncertain FEA-predicted workpiece modal parameters. The experimentally identified cutting force coefficients were also treated as uncertain inputs. Physical cutting tests on a constrained motion dynamometer system were then used to retain or reject candidate maps based on the observed stable/unstable outcomes. The candidate maps were reduced from 10,000 to 6 after five partitioning steps, and the retained maps moved toward the tap-tested reference stability map. These results demonstrate that sample partitioning can reduce uncertainty in FEA-based stability maps using a limited number of cutting tests. 2026-06-23 JMMP, Vol. 10, Pages 215: Sample Partitioning for Uncertainty Reduction in FEA-Based Milling Stability Prediction

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10070215

Authors: Junbeom Son Uday Vaidya Tony Schmitz

Milling stability prediction requires tool and workpiece dynamics and cutting force coefficients, and uncertainty in these inputs propagates to the predicted stability maps. This study experimentally evaluates sample partitioning for uncertainty reduction in milling stability when the workpiece dynamics are predicted using finite element analysis (FEA). The FEA-predicted workpiece natural frequency and modal stiffness differed from the tap-tested reference values by 4.9% and 14.3%, respectively, leading to different predicted stability maps. Initial candidate stability maps were generated by Monte Carlo simulation using the uncertain FEA-predicted workpiece modal parameters. The experimentally identified cutting force coefficients were also treated as uncertain inputs. Physical cutting tests on a constrained motion dynamometer system were then used to retain or reject candidate maps based on the observed stable/unstable outcomes. The candidate maps were reduced from 10,000 to 6 after five partitioning steps, and the retained maps moved toward the tap-tested reference stability map. These results demonstrate that sample partitioning can reduce uncertainty in FEA-based stability maps using a limited number of cutting tests.

]]> Sample Partitioning for Uncertainty Reduction in FEA-Based Milling Stability Prediction Junbeom Son Uday Vaidya Tony Schmitz doi: 10.3390/jmmp10070215 Journal of Manufacturing and Materials Processing 2026-06-23 Journal of Manufacturing and Materials Processing 2026-06-23 10 7 Article 215 10.3390/jmmp10070215 https://www.mdpi.com/2504-4494/10/7/215 JMMP, Vol. 10, Pages 214: Challenges and Opportunities in Friction-Based Additive Manufacturing of Heat-Treatable Aluminum Alloys https://www.mdpi.com/2504-4494/10/6/214 Heat-treatable aluminum alloys are widely used in aerospace and automotive industries for high-performance structural applications. However, their processing through conventional fusion-based additive manufacturing is limited by solidification-related defects, such as hot cracking, porosity, and elemental segregation. To overcome these limitations, friction-based additive manufacturing (FBAM) has emerged as a promising solid-state alternative. FBAM primarily includes friction stir additive manufacturing (FSAM), additive friction stir deposition (AFSD), friction screw extrusion additive manufacturing (FSEAM), and friction rolling additive manufacturing (FRAM), which differ in feedstock form and process configuration. In these processes, feed material is consolidated through frictional heat generated below the melting temperature, enabling the formation of refined equiaxed microstructures while minimizing solidification defects. Despite these advantages, significant challenges persist in processing heat-treatable aluminum alloys, particularly the 2xxx, 6xxx, and 7xxx series. These include non-uniform microstructure and mechanical properties along the build direction; precipitation instability; process-induced defects, such as tunnel formation; and mechanical properties that are often inferior to those of the corresponding base materials (BMs). Reported FBAM builds generally exhibit equiaxed ultrafine grains below 1 μm; however, the strength and microhardness of heat-treated alloy builds commonly remain around 70–75% of the corresponding BM. Following post-heat treatment, microhardness can be nearly fully recovered, whereas UTS typically reaches about 80–85% of BMs, often with an associated ductility reduction of nearly 50%. This review critically analyzes research reported over the past decade on FBAM processing of heat-treatable aluminum alloys, covering FSAM, AFSD, FSEAM, and FRAM. The key challenges related to microstructural evolution and mechanical performance are systematically discussed for each alloy series. Furthermore, mitigation strategies proposed in the literature, including process parameter optimization, in-process cooling, post-heat treatment, and nanoparticle reinforcement (e.g., SiC, TiC, Ni and ZrO2), are evaluated. Finally, existing research gaps are identified, and future directions are proposed to support the development of robust, scalable, and high-performance FBAM processes for heat-treatable aluminum alloys. 2026-06-21 JMMP, Vol. 10, Pages 214: Challenges and Opportunities in Friction-Based Additive Manufacturing of Heat-Treatable Aluminum Alloys

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060214

Authors: Adeel Hassan Mokhtar Che Ismail Srinivasa Rao Pedapati Roshan Vijay Marode Khurram Altaf Santoshi Pedapati

Heat-treatable aluminum alloys are widely used in aerospace and automotive industries for high-performance structural applications. However, their processing through conventional fusion-based additive manufacturing is limited by solidification-related defects, such as hot cracking, porosity, and elemental segregation. To overcome these limitations, friction-based additive manufacturing (FBAM) has emerged as a promising solid-state alternative. FBAM primarily includes friction stir additive manufacturing (FSAM), additive friction stir deposition (AFSD), friction screw extrusion additive manufacturing (FSEAM), and friction rolling additive manufacturing (FRAM), which differ in feedstock form and process configuration. In these processes, feed material is consolidated through frictional heat generated below the melting temperature, enabling the formation of refined equiaxed microstructures while minimizing solidification defects. Despite these advantages, significant challenges persist in processing heat-treatable aluminum alloys, particularly the 2xxx, 6xxx, and 7xxx series. These include non-uniform microstructure and mechanical properties along the build direction; precipitation instability; process-induced defects, such as tunnel formation; and mechanical properties that are often inferior to those of the corresponding base materials (BMs). Reported FBAM builds generally exhibit equiaxed ultrafine grains below 1 μm; however, the strength and microhardness of heat-treated alloy builds commonly remain around 70–75% of the corresponding BM. Following post-heat treatment, microhardness can be nearly fully recovered, whereas UTS typically reaches about 80–85% of BMs, often with an associated ductility reduction of nearly 50%. This review critically analyzes research reported over the past decade on FBAM processing of heat-treatable aluminum alloys, covering FSAM, AFSD, FSEAM, and FRAM. The key challenges related to microstructural evolution and mechanical performance are systematically discussed for each alloy series. Furthermore, mitigation strategies proposed in the literature, including process parameter optimization, in-process cooling, post-heat treatment, and nanoparticle reinforcement (e.g., SiC, TiC, Ni and ZrO2), are evaluated. Finally, existing research gaps are identified, and future directions are proposed to support the development of robust, scalable, and high-performance FBAM processes for heat-treatable aluminum alloys.

]]> Challenges and Opportunities in Friction-Based Additive Manufacturing of Heat-Treatable Aluminum Alloys Adeel Hassan Mokhtar Che Ismail Srinivasa Rao Pedapati Roshan Vijay Marode Khurram Altaf Santoshi Pedapati doi: 10.3390/jmmp10060214 Journal of Manufacturing and Materials Processing 2026-06-21 Journal of Manufacturing and Materials Processing 2026-06-21 10 6 Review 214 10.3390/jmmp10060214 https://www.mdpi.com/2504-4494/10/6/214 JMMP, Vol. 10, Pages 213: Efficient Prediction of Cutting Force and Stability in Five-Axis Machining of Complex Surfaces Based on Dimensional Compression https://www.mdpi.com/2504-4494/10/6/213 With the rapid development of high-end equipment manufacturing, the number and size of complex surfaces continue to increase. Five-axis machining has become the dominant machining method. Effective prediction of cutting force and stability is of great significance for improving machining efficiency and quality. However, due to the complex and time-varying cutting geometry in five-axis machining of complex surfaces, low prediction efficiency has become a key issue restricting the research and engineering application of cutting force and stability. To address this issue, this study introduces the concept of dimensional compression and establishes an efficient prediction model for cutting force and stability. Each tool position along the tool path is discretized into inclined plane milling based on finite difference, thereby simplifying the research object. The tool twist angle and feed deflection angle are defined to describe the spatial relationship in five-axis machining. Using these two angles as new basis variables, a compressed space is constructed, and a mapping relationship between tool position and spatial point sets is established, further reducing the dimensionality of the research object. The cutting edge contact interval is determined using the spatial constraint method. Based on the full discretization method, the cutting force and stability of inclined plane milling are predicted, and the results are uniformly stored in the compressed space to form a sample point library. Consequently, the prediction process of complex surface five-axis machining is transformed into a process of sample point retrieval, significantly improving computational efficiency. Cutting force and vibration experiments in five-axis machining of complex surfaces are conducted. The results show that the predicted results are in good agreement with the experimental measurements, validating the accuracy of the proposed model and demonstrating its capability to guide practical machining. 2026-06-16 JMMP, Vol. 10, Pages 213: Efficient Prediction of Cutting Force and Stability in Five-Axis Machining of Complex Surfaces Based on Dimensional Compression

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060213

Authors: Jingyang Feng Jianning Zhu Minglong Guo Xiuru Li Xueqin Wang

With the rapid development of high-end equipment manufacturing, the number and size of complex surfaces continue to increase. Five-axis machining has become the dominant machining method. Effective prediction of cutting force and stability is of great significance for improving machining efficiency and quality. However, due to the complex and time-varying cutting geometry in five-axis machining of complex surfaces, low prediction efficiency has become a key issue restricting the research and engineering application of cutting force and stability. To address this issue, this study introduces the concept of dimensional compression and establishes an efficient prediction model for cutting force and stability. Each tool position along the tool path is discretized into inclined plane milling based on finite difference, thereby simplifying the research object. The tool twist angle and feed deflection angle are defined to describe the spatial relationship in five-axis machining. Using these two angles as new basis variables, a compressed space is constructed, and a mapping relationship between tool position and spatial point sets is established, further reducing the dimensionality of the research object. The cutting edge contact interval is determined using the spatial constraint method. Based on the full discretization method, the cutting force and stability of inclined plane milling are predicted, and the results are uniformly stored in the compressed space to form a sample point library. Consequently, the prediction process of complex surface five-axis machining is transformed into a process of sample point retrieval, significantly improving computational efficiency. Cutting force and vibration experiments in five-axis machining of complex surfaces are conducted. The results show that the predicted results are in good agreement with the experimental measurements, validating the accuracy of the proposed model and demonstrating its capability to guide practical machining.

]]> Efficient Prediction of Cutting Force and Stability in Five-Axis Machining of Complex Surfaces Based on Dimensional Compression Jingyang Feng Jianning Zhu Minglong Guo Xiuru Li Xueqin Wang doi: 10.3390/jmmp10060213 Journal of Manufacturing and Materials Processing 2026-06-16 Journal of Manufacturing and Materials Processing 2026-06-16 10 6 Article 213 10.3390/jmmp10060213 https://www.mdpi.com/2504-4494/10/6/213 JMMP, Vol. 10, Pages 212: Determinants of AI-Enabled Quality Control Adoption Intention in Manufacturing SMEs: An Integrated TOE–TAM Analysis Using PLS-SEM, IPMA, and fsQCA https://www.mdpi.com/2504-4494/10/6/212 AI-enabled quality control (AI-QC) tools are increasingly available to manufacturing SMEs in emerging economies, yet the firm-level conditions associated with their adoption remain underexamined. Building on the Technology–Organization–Environment (TOE) framework of Tornatzky and Fleischer, integrated with the perceived usefulness and perceived ease-of-use constructs of the Technology Acceptance Model (TAM), this study examines the determinants of AI-QC adoption intention, and its association with operational performance improvement, in 284 manufacturing SMEs from Turkey, Malaysia, and Egypt. The focal dependent construct is adoption intention rather than realized adoption. The AI-QC technologies considered are machine learning defect detection, computer vision inspection, predictive maintenance, and digital twin integration. Three complementary analytical procedures are applied to the same data: partial least squares structural equation modeling (PLS-SEM) to estimate the strength of the modeled associations, importance–performance map analysis (IPMA) to identify high-importance but low-performance predictors, and fuzzy-set qualitative comparative analysis (fsQCA) to identify combinations of conditions jointly sufficient for high adoption intention. The PLS-SEM estimates indicate positive associations for the technological, organizational, and environmental predictors, with top management support, perceived usefulness, and organizational readiness showing the largest coefficients and data security concern showing a negative association; effect magnitudes varied considerably, and several were small. The IPMA results indicate that the two most important predictors exhibit comparatively low performance scores in the sample. The fsQCA results identify three configurations associated with high adoption intention. Because the design is cross-sectional and based on self-reported, single-respondent data, the findings are interpreted as associations rather than causal effects. The paper concludes with guidance for SME managers, AI technology vendors, and industrial policymakers. 2026-06-16 JMMP, Vol. 10, Pages 212: Determinants of AI-Enabled Quality Control Adoption Intention in Manufacturing SMEs: An Integrated TOE–TAM Analysis Using PLS-SEM, IPMA, and fsQCA

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060212

Authors: Haldun Turan

AI-enabled quality control (AI-QC) tools are increasingly available to manufacturing SMEs in emerging economies, yet the firm-level conditions associated with their adoption remain underexamined. Building on the Technology–Organization–Environment (TOE) framework of Tornatzky and Fleischer, integrated with the perceived usefulness and perceived ease-of-use constructs of the Technology Acceptance Model (TAM), this study examines the determinants of AI-QC adoption intention, and its association with operational performance improvement, in 284 manufacturing SMEs from Turkey, Malaysia, and Egypt. The focal dependent construct is adoption intention rather than realized adoption. The AI-QC technologies considered are machine learning defect detection, computer vision inspection, predictive maintenance, and digital twin integration. Three complementary analytical procedures are applied to the same data: partial least squares structural equation modeling (PLS-SEM) to estimate the strength of the modeled associations, importance–performance map analysis (IPMA) to identify high-importance but low-performance predictors, and fuzzy-set qualitative comparative analysis (fsQCA) to identify combinations of conditions jointly sufficient for high adoption intention. The PLS-SEM estimates indicate positive associations for the technological, organizational, and environmental predictors, with top management support, perceived usefulness, and organizational readiness showing the largest coefficients and data security concern showing a negative association; effect magnitudes varied considerably, and several were small. The IPMA results indicate that the two most important predictors exhibit comparatively low performance scores in the sample. The fsQCA results identify three configurations associated with high adoption intention. Because the design is cross-sectional and based on self-reported, single-respondent data, the findings are interpreted as associations rather than causal effects. The paper concludes with guidance for SME managers, AI technology vendors, and industrial policymakers.

]]> Determinants of AI-Enabled Quality Control Adoption Intention in Manufacturing SMEs: An Integrated TOE–TAM Analysis Using PLS-SEM, IPMA, and fsQCA Haldun Turan doi: 10.3390/jmmp10060212 Journal of Manufacturing and Materials Processing 2026-06-16 Journal of Manufacturing and Materials Processing 2026-06-16 10 6 Article 212 10.3390/jmmp10060212 https://www.mdpi.com/2504-4494/10/6/212 JMMP, Vol. 10, Pages 209: Energy Efficiency-Driven Selection of Wireless Communication Stacks for Industrial Retrofitting Applications https://www.mdpi.com/2504-4494/10/6/209 The digital integration of existing industrial equipment (retrofitting) is a central element of the Industry 4.0 paradigm, wherein the energy efficiency of Internet of Things (IoT) gateways is a decisive design consideration. This research aims to experimentally compare various wireless and wired communication protocols—ESP-NOW, Bluetooth Low Energy (BLE), Bluetooth Classic (Serial Port Profile, SPP), Message Queuing Telemetry Transport (MQTT), and S7 Protocol—within a legacy Programmable Logic Controller (PLC)-based environment. A dedicated testbed was developed using Siemens S7-300 PLCs and ESP32-based gateway devices to ensure measurement reproducibility. Energy consumption was determined using a high-precision power profiler with payloads ranging from 50 to 15,000 bytes, applying the trapezoidal rule while considering both active transaction and standby states. The specific energy consumption metric (μJ/byte) introduced in this study highlights the distinct scaling limitations of the protocols. While ESP-NOW proved highly efficient for small telemetry packets, Bluetooth Classic exhibited superior scalability for bulk data volumes. Furthermore, a critical energetic crossover point was identified for ESP-NOW due to hardware fragmentation limits, whereas MQTT demonstrated massive energetic overhead for small payloads. Standby measurements confirmed that the continuous baseline consumption of the wired Ethernet interface significantly dominates the energy budget compared to wireless alternatives. These empirical findings are synthesized into a formal Qualitative Decision Matrix to help engineers optimize protocol selection based on the expected duty cycle, facilitating the development of sustainable industrial digitalization solutions. 2026-06-16 JMMP, Vol. 10, Pages 209: Energy Efficiency-Driven Selection of Wireless Communication Stacks for Industrial Retrofitting Applications

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060209

Authors: Richárd Korpai Norbert Szántó Gergő Dávid Monek

The digital integration of existing industrial equipment (retrofitting) is a central element of the Industry 4.0 paradigm, wherein the energy efficiency of Internet of Things (IoT) gateways is a decisive design consideration. This research aims to experimentally compare various wireless and wired communication protocols—ESP-NOW, Bluetooth Low Energy (BLE), Bluetooth Classic (Serial Port Profile, SPP), Message Queuing Telemetry Transport (MQTT), and S7 Protocol—within a legacy Programmable Logic Controller (PLC)-based environment. A dedicated testbed was developed using Siemens S7-300 PLCs and ESP32-based gateway devices to ensure measurement reproducibility. Energy consumption was determined using a high-precision power profiler with payloads ranging from 50 to 15,000 bytes, applying the trapezoidal rule while considering both active transaction and standby states. The specific energy consumption metric (μJ/byte) introduced in this study highlights the distinct scaling limitations of the protocols. While ESP-NOW proved highly efficient for small telemetry packets, Bluetooth Classic exhibited superior scalability for bulk data volumes. Furthermore, a critical energetic crossover point was identified for ESP-NOW due to hardware fragmentation limits, whereas MQTT demonstrated massive energetic overhead for small payloads. Standby measurements confirmed that the continuous baseline consumption of the wired Ethernet interface significantly dominates the energy budget compared to wireless alternatives. These empirical findings are synthesized into a formal Qualitative Decision Matrix to help engineers optimize protocol selection based on the expected duty cycle, facilitating the development of sustainable industrial digitalization solutions.

]]> Energy Efficiency-Driven Selection of Wireless Communication Stacks for Industrial Retrofitting Applications Richárd Korpai Norbert Szántó Gergő Dávid Monek doi: 10.3390/jmmp10060209 Journal of Manufacturing and Materials Processing 2026-06-16 Journal of Manufacturing and Materials Processing 2026-06-16 10 6 Article 209 10.3390/jmmp10060209 https://www.mdpi.com/2504-4494/10/6/209 JMMP, Vol. 10, Pages 211: Research on On-Line Precision Measurement System of Rolling Bearing Roundness https://www.mdpi.com/2504-4494/10/6/211 High-precision rolling bearing applications are widely used in aerospace, new energy vehicles and high-end equipment. However, high-precision bearing manufacturing has always been one of the hot topics of research. The main problem is that the grinding accuracy of rolling bearings is too divergent. In this study, the improvement of grinding accuracy of high-precision rolling bearings was mainly studied. An on-line roundness measurement system was developed and its accuracy was analyzed. The same bearing precision grade, different bearing brands, different bearing sizes and different measurement methods were mainly used for cross-precision measurement comparison. Meanwhile, a static analysis was conducted on the measuring claw. Results indicate that the on-line measurement system can achieve an accuracy of 3 µm. The error rate was less than 11% compared with the current mature measurement technology. Under the action of the same normal measuring force, the deformation of the measuring claw of invar was larger than that of the measuring claw of 45 steel, which was relatively increased by 31%. The conclusion of this study will provide reliable data analysis and a theoretical basis for research in the field of bearing. 2026-06-16 JMMP, Vol. 10, Pages 211: Research on On-Line Precision Measurement System of Rolling Bearing Roundness

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060211

Authors: Lei Zhao Hui Chen Jianzuo Ma Chuanbing Wang Lai Hu

High-precision rolling bearing applications are widely used in aerospace, new energy vehicles and high-end equipment. However, high-precision bearing manufacturing has always been one of the hot topics of research. The main problem is that the grinding accuracy of rolling bearings is too divergent. In this study, the improvement of grinding accuracy of high-precision rolling bearings was mainly studied. An on-line roundness measurement system was developed and its accuracy was analyzed. The same bearing precision grade, different bearing brands, different bearing sizes and different measurement methods were mainly used for cross-precision measurement comparison. Meanwhile, a static analysis was conducted on the measuring claw. Results indicate that the on-line measurement system can achieve an accuracy of 3 µm. The error rate was less than 11% compared with the current mature measurement technology. Under the action of the same normal measuring force, the deformation of the measuring claw of invar was larger than that of the measuring claw of 45 steel, which was relatively increased by 31%. The conclusion of this study will provide reliable data analysis and a theoretical basis for research in the field of bearing.

]]> Research on On-Line Precision Measurement System of Rolling Bearing Roundness Lei Zhao Hui Chen Jianzuo Ma Chuanbing Wang Lai Hu doi: 10.3390/jmmp10060211 Journal of Manufacturing and Materials Processing 2026-06-16 Journal of Manufacturing and Materials Processing 2026-06-16 10 6 Article 211 10.3390/jmmp10060211 https://www.mdpi.com/2504-4494/10/6/211 JMMP, Vol. 10, Pages 210: Influence of Deposition Strategy and Fiber Alignment on the Mechanical Anisotropy of Short-Fiber-Reinforced Polyamide Manufactured by Additive Manufacturing Material Extrusion https://www.mdpi.com/2504-4494/10/6/210 Short-fiber-reinforced composites (SFRCs) are widely used for their high strength-to-weight ratio. In the Additive Manufacturing (AM) field, Material Extrusion (MEX) processes inherently induce anisotropy, primarily due to fiber alignment along the deposition path, making printing direction and layer orientation critical for mechanical performance. In this study, specimens made of Onyx®, a carbon short-fiber-reinforced polyamide, were fabricated by varying their orientation on the build platform, thereby producing different infill deposition directions. Each replica contained 25 layers. Two deposition strategies were investigated: a conventional alternating ±45° raster pattern and a 0°/90° configuration. Owing to the odd number of deposited layers, the latter resulted in two distinct stacking configurations, namely 0°/90° and 90°/0°, depending on the orientation of the first deposited layer. With such a strategy, it was possible to obtain configurations with a predominance of fibers either aligned with or transverse to the loading direction, depending on the orientation of the first-deposited layer. Mechanical test results were systematically compared to evaluate the influence of deposition strategy and fiber orientation on tensile performances. The effect of extrusion on fiber alignment was evaluated using Scanning Electron Microscopy (SEM). Mechanical behavior was evaluated using replicated tensile testing (five specimens per condition) and SEM-based fiber-orientation analysis. The investigation confirms the anisotropic nature of MEX-produced SFRCs. In particular, the 0°/90° configuration showed reductions of approximately 24% in tensile strength and 58% in elongation at break compared with the ±45° configuration. These results demonstrate that both extrusion-induced fiber orientation and layer-wise deposition strategy play a crucial role in defining the mechanical response of the material. 2026-06-16 JMMP, Vol. 10, Pages 210: Influence of Deposition Strategy and Fiber Alignment on the Mechanical Anisotropy of Short-Fiber-Reinforced Polyamide Manufactured by Additive Manufacturing Material Extrusion

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060210

Authors: Andrea Colucci Manuela Galati Luca Iuliano

Short-fiber-reinforced composites (SFRCs) are widely used for their high strength-to-weight ratio. In the Additive Manufacturing (AM) field, Material Extrusion (MEX) processes inherently induce anisotropy, primarily due to fiber alignment along the deposition path, making printing direction and layer orientation critical for mechanical performance. In this study, specimens made of Onyx®, a carbon short-fiber-reinforced polyamide, were fabricated by varying their orientation on the build platform, thereby producing different infill deposition directions. Each replica contained 25 layers. Two deposition strategies were investigated: a conventional alternating ±45° raster pattern and a 0°/90° configuration. Owing to the odd number of deposited layers, the latter resulted in two distinct stacking configurations, namely 0°/90° and 90°/0°, depending on the orientation of the first deposited layer. With such a strategy, it was possible to obtain configurations with a predominance of fibers either aligned with or transverse to the loading direction, depending on the orientation of the first-deposited layer. Mechanical test results were systematically compared to evaluate the influence of deposition strategy and fiber orientation on tensile performances. The effect of extrusion on fiber alignment was evaluated using Scanning Electron Microscopy (SEM). Mechanical behavior was evaluated using replicated tensile testing (five specimens per condition) and SEM-based fiber-orientation analysis. The investigation confirms the anisotropic nature of MEX-produced SFRCs. In particular, the 0°/90° configuration showed reductions of approximately 24% in tensile strength and 58% in elongation at break compared with the ±45° configuration. These results demonstrate that both extrusion-induced fiber orientation and layer-wise deposition strategy play a crucial role in defining the mechanical response of the material.

]]> Influence of Deposition Strategy and Fiber Alignment on the Mechanical Anisotropy of Short-Fiber-Reinforced Polyamide Manufactured by Additive Manufacturing Material Extrusion Andrea Colucci Manuela Galati Luca Iuliano doi: 10.3390/jmmp10060210 Journal of Manufacturing and Materials Processing 2026-06-16 Journal of Manufacturing and Materials Processing 2026-06-16 10 6 Article 210 10.3390/jmmp10060210 https://www.mdpi.com/2504-4494/10/6/210 JMMP, Vol. 10, Pages 208: Effect of Sintering Temperature and Artificial Aging on the Microstructure and Mechanical Properties of AlSi10Mg Alloy https://www.mdpi.com/2504-4494/10/6/208 This study investigates the correlation between sintering temperature, microstructure, and mechanical properties in AlSi10Mg alloy produced by supersolidus liquid phase sintering and subsequent artificial aging. Sintering was performed at 571, 575, and 579 °C using different heating rates for a total duration of approximately 5 h, followed by a 2 h dwell at the sintering temperature. At low sintering temperature, the alloy exhibits relatively fine α-Al grains with uniformly distributed Si precipitates, whereas intermediate temperature promotes Si coarsening. At higher temperature, excessive liquid formation leads to coarse α-Al grains and the development of partially interconnected Si networks. β-Al5FeSi progressively coarsen with increasing sintering temperature. In the as-sintered state, the modest mechanical properties result from coarse α-Al grain size and subgrain structure, as well as from the size, morphology, and distribution of the Si phase. After aging (at 160 °C for 6 h following solution treatment at 530 °C for 30 min), the hardness and UTS were almost double (going from 44 ± 1 to 103 ± 2 HV and from 121 ± 1 to 273 ± 40 MPa). Meanwhile, α-Al grain size and Si morphology remained unchanged and Fe-rich intermetallics partially transformed into the more stable γ-Al3FeSi2 phase. 2026-06-15 JMMP, Vol. 10, Pages 208: Effect of Sintering Temperature and Artificial Aging on the Microstructure and Mechanical Properties of AlSi10Mg Alloy

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060208

Authors: Mohamed Khaled Trigui Alena Kreitcberg Abdelberi Chandoul Roger Pelletier Vincent Demers

This study investigates the correlation between sintering temperature, microstructure, and mechanical properties in AlSi10Mg alloy produced by supersolidus liquid phase sintering and subsequent artificial aging. Sintering was performed at 571, 575, and 579 °C using different heating rates for a total duration of approximately 5 h, followed by a 2 h dwell at the sintering temperature. At low sintering temperature, the alloy exhibits relatively fine α-Al grains with uniformly distributed Si precipitates, whereas intermediate temperature promotes Si coarsening. At higher temperature, excessive liquid formation leads to coarse α-Al grains and the development of partially interconnected Si networks. β-Al5FeSi progressively coarsen with increasing sintering temperature. In the as-sintered state, the modest mechanical properties result from coarse α-Al grain size and subgrain structure, as well as from the size, morphology, and distribution of the Si phase. After aging (at 160 °C for 6 h following solution treatment at 530 °C for 30 min), the hardness and UTS were almost double (going from 44 ± 1 to 103 ± 2 HV and from 121 ± 1 to 273 ± 40 MPa). Meanwhile, α-Al grain size and Si morphology remained unchanged and Fe-rich intermetallics partially transformed into the more stable γ-Al3FeSi2 phase.

]]> Effect of Sintering Temperature and Artificial Aging on the Microstructure and Mechanical Properties of AlSi10Mg Alloy Mohamed Khaled Trigui Alena Kreitcberg Abdelberi Chandoul Roger Pelletier Vincent Demers doi: 10.3390/jmmp10060208 Journal of Manufacturing and Materials Processing 2026-06-15 Journal of Manufacturing and Materials Processing 2026-06-15 10 6 Article 208 10.3390/jmmp10060208 https://www.mdpi.com/2504-4494/10/6/208 JMMP, Vol. 10, Pages 207: Machine Learning-Based Analysis of Elastic Springback in Bending of SS, Al, and Cu Sheets with Localized Heating https://www.mdpi.com/2504-4494/10/6/207 Elastic springback is a critical challenge in sheet metal bending that directly affects dimensional accuracy and manufacturing efficiency. This study presents a comparative experimental and machine learning-based analysis of elastic springback behavior in three widely used sheet metals like stainless steel, aluminum, and copper, which are subjected to folding bending. The influence of key process parameters, namely sheet thickness (0.5 to 1.5 mm) and bending temperature (room temperature to 200 °C), was systematically examined under cold working. A cost-effective localized heating approach using a direct flame was introduced to enhance process control and reduce elastic recovery without the complexity associated with heated dies. Experimental results revealed substantial variability in elastic springback, ranging from 0.15% to 12.41%, emphasizing the fact that they are nonlinear in nature. Statistical evaluation confirmed that sheet thickness is the dominant factor governing elastic springback, while material type and temperature exhibit secondary yet meaningful effects. To improve predictive capability, five regression models (Linear, Polynomial, Support Vector, Random Forest, and Gradient Boosting) were developed and assessed. Among them, Random Forest demonstrated superior performance with the lowest prediction errors and strongest explanatory power, achieving an R2 of approximately 0.85. Cross-validation further validated its robustness and generalization capability. Feature importance and SHapley Additive exPlanations (SHAP) analyses reinforced the primary role of thickness in determining elastic recovery behavior. The findings provide practical insights for selecting materials and process conditions to minimize elastic springback while highlighting the effectiveness of ensemble learning techniques for accurate prediction. This work contributes a consistent framework for enhancing bending precision and supports data-driven decision-making in modern manufacturing environments. 2026-06-14 JMMP, Vol. 10, Pages 207: Machine Learning-Based Analysis of Elastic Springback in Bending of SS, Al, and Cu Sheets with Localized Heating

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060207

Authors: Naser A. Alsaleh

Elastic springback is a critical challenge in sheet metal bending that directly affects dimensional accuracy and manufacturing efficiency. This study presents a comparative experimental and machine learning-based analysis of elastic springback behavior in three widely used sheet metals like stainless steel, aluminum, and copper, which are subjected to folding bending. The influence of key process parameters, namely sheet thickness (0.5 to 1.5 mm) and bending temperature (room temperature to 200 °C), was systematically examined under cold working. A cost-effective localized heating approach using a direct flame was introduced to enhance process control and reduce elastic recovery without the complexity associated with heated dies. Experimental results revealed substantial variability in elastic springback, ranging from 0.15% to 12.41%, emphasizing the fact that they are nonlinear in nature. Statistical evaluation confirmed that sheet thickness is the dominant factor governing elastic springback, while material type and temperature exhibit secondary yet meaningful effects. To improve predictive capability, five regression models (Linear, Polynomial, Support Vector, Random Forest, and Gradient Boosting) were developed and assessed. Among them, Random Forest demonstrated superior performance with the lowest prediction errors and strongest explanatory power, achieving an R2 of approximately 0.85. Cross-validation further validated its robustness and generalization capability. Feature importance and SHapley Additive exPlanations (SHAP) analyses reinforced the primary role of thickness in determining elastic recovery behavior. The findings provide practical insights for selecting materials and process conditions to minimize elastic springback while highlighting the effectiveness of ensemble learning techniques for accurate prediction. This work contributes a consistent framework for enhancing bending precision and supports data-driven decision-making in modern manufacturing environments.

]]> Machine Learning-Based Analysis of Elastic Springback in Bending of SS, Al, and Cu Sheets with Localized Heating Naser A. Alsaleh doi: 10.3390/jmmp10060207 Journal of Manufacturing and Materials Processing 2026-06-14 Journal of Manufacturing and Materials Processing 2026-06-14 10 6 Article 207 10.3390/jmmp10060207 https://www.mdpi.com/2504-4494/10/6/207 JMMP, Vol. 10, Pages 206: Dynamic Modeling and Chatter Stability of a Robotic Milling Manipulator Considering the Flexibility of Arms and Joints https://www.mdpi.com/2504-4494/10/6/206 The application of robotic milling manipulators demonstrates a promising method for the efficient manufacturing of large-scale structures. However, the cutting accuracy and efficiency of milling robots are predominantly subjected to their low stiffness, which may easily cause chatter during machining. Accurate prediction of chatter stability for robots is of practical importance and is challenging. This paper develops a dynamic model of flexible link elements by considering link flexibility and joint torsional deformation and then constructs a multi-link flexible coupled dynamic model using the receptance coupling substructure analysis (RCSA) method. Subsequently, the equivalent dynamic parameters are identified via the particle swarm optimization (PSO) algorithm. On this basis, the end-effector frequency response functions (FRFs) of the robot under different poses are predicted, and the stability lobe diagram (SLD) for milling is generated based on chatter theory. Finally, the predicted FRFs and stability regions are validated through modal tests and milling experiments. Experimental results demonstrate that the proposed model can predict the end-effector dynamic characteristics and chatter occurrence conditions under different poses, confirming its effectiveness in the analysis of milling chatter stability. Quantitative validation yields a maximum error of 3% for predicted first-order modal frequencies and relative modal amplitude errors below 10%, with experimentally confirmed critical depths of cut of 0.1–0.2 mm at 3000 rev/min and 0.5–0.6 mm at 5000 rev/min. 2026-06-14 JMMP, Vol. 10, Pages 206: Dynamic Modeling and Chatter Stability of a Robotic Milling Manipulator Considering the Flexibility of Arms and Joints

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060206

Authors: Chao Chen Jingjun Yu Yiqing Yang Wenjing Wu Wenshuo Ma

The application of robotic milling manipulators demonstrates a promising method for the efficient manufacturing of large-scale structures. However, the cutting accuracy and efficiency of milling robots are predominantly subjected to their low stiffness, which may easily cause chatter during machining. Accurate prediction of chatter stability for robots is of practical importance and is challenging. This paper develops a dynamic model of flexible link elements by considering link flexibility and joint torsional deformation and then constructs a multi-link flexible coupled dynamic model using the receptance coupling substructure analysis (RCSA) method. Subsequently, the equivalent dynamic parameters are identified via the particle swarm optimization (PSO) algorithm. On this basis, the end-effector frequency response functions (FRFs) of the robot under different poses are predicted, and the stability lobe diagram (SLD) for milling is generated based on chatter theory. Finally, the predicted FRFs and stability regions are validated through modal tests and milling experiments. Experimental results demonstrate that the proposed model can predict the end-effector dynamic characteristics and chatter occurrence conditions under different poses, confirming its effectiveness in the analysis of milling chatter stability. Quantitative validation yields a maximum error of 3% for predicted first-order modal frequencies and relative modal amplitude errors below 10%, with experimentally confirmed critical depths of cut of 0.1–0.2 mm at 3000 rev/min and 0.5–0.6 mm at 5000 rev/min.

]]> Dynamic Modeling and Chatter Stability of a Robotic Milling Manipulator Considering the Flexibility of Arms and Joints Chao Chen Jingjun Yu Yiqing Yang Wenjing Wu Wenshuo Ma doi: 10.3390/jmmp10060206 Journal of Manufacturing and Materials Processing 2026-06-14 Journal of Manufacturing and Materials Processing 2026-06-14 10 6 Article 206 10.3390/jmmp10060206 https://www.mdpi.com/2504-4494/10/6/206 JMMP, Vol. 10, Pages 205: Microstructural Evolution and Mechanical Behavior of L-PBF Al-Cu 224 Alloy: Role of Process Parameters and Heat Treatment https://www.mdpi.com/2504-4494/10/6/205 This study investigates the effect of laser powder bed fusion (L-PBF) parameters and T7 heat treatment on the defect formation, microstructure, and mechanical properties of a high-strength Al-Cu 224 aluminum alloy. The laser power (200–370 W), scanning speed (130–1900 mm/s), and hatch spacing (90–130 μm) were varied to evaluate their influence on hot cracking and porosity. Microstructural characterization using optical microscopy, scanning electron microscopy, and electron backscatter diffraction revealed that an energy density of 400 J/mm3 substantially reduced visible hot cracking in the examined microscopic regions by reducing the thermal gradients. However, this resulted in increased keyhole porosity, thereby limiting the relative density to 95%. The as-built samples exhibited a yield strength of 152 MPa and an elongation of 9.2%, and the T7 heat treatment improved the yield strength to 233 MPa, whereas the elongation remained unchanged. Keyhole pores served as primary crack initiation/propagation sites during tensile loading, reducing ductility. Lower energy densities increased the geometrically necessary dislocation density and promoted cracking because of higher residual stresses due to greater accumulated plastic strain and lattice curvature. These results clarify process–structure–property relationships, emphasize the trade-offs between defect types and performance, and provide a robust framework for optimizing L-PBF processing of high-strength Al alloys through parameter tuning and post-heat treatment. 2026-06-12 JMMP, Vol. 10, Pages 205: Microstructural Evolution and Mechanical Behavior of L-PBF Al-Cu 224 Alloy: Role of Process Parameters and Heat Treatment

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060205

Authors: Esmaeil Pourkhorshid Paul Rometsch Mousa Javidani Alexandre Bily X.-Grant Chen

This study investigates the effect of laser powder bed fusion (L-PBF) parameters and T7 heat treatment on the defect formation, microstructure, and mechanical properties of a high-strength Al-Cu 224 aluminum alloy. The laser power (200–370 W), scanning speed (130–1900 mm/s), and hatch spacing (90–130 μm) were varied to evaluate their influence on hot cracking and porosity. Microstructural characterization using optical microscopy, scanning electron microscopy, and electron backscatter diffraction revealed that an energy density of 400 J/mm3 substantially reduced visible hot cracking in the examined microscopic regions by reducing the thermal gradients. However, this resulted in increased keyhole porosity, thereby limiting the relative density to 95%. The as-built samples exhibited a yield strength of 152 MPa and an elongation of 9.2%, and the T7 heat treatment improved the yield strength to 233 MPa, whereas the elongation remained unchanged. Keyhole pores served as primary crack initiation/propagation sites during tensile loading, reducing ductility. Lower energy densities increased the geometrically necessary dislocation density and promoted cracking because of higher residual stresses due to greater accumulated plastic strain and lattice curvature. These results clarify process–structure–property relationships, emphasize the trade-offs between defect types and performance, and provide a robust framework for optimizing L-PBF processing of high-strength Al alloys through parameter tuning and post-heat treatment.

]]> Microstructural Evolution and Mechanical Behavior of L-PBF Al-Cu 224 Alloy: Role of Process Parameters and Heat Treatment Esmaeil Pourkhorshid Paul Rometsch Mousa Javidani Alexandre Bily X.-Grant Chen doi: 10.3390/jmmp10060205 Journal of Manufacturing and Materials Processing 2026-06-12 Journal of Manufacturing and Materials Processing 2026-06-12 10 6 Article 205 10.3390/jmmp10060205 https://www.mdpi.com/2504-4494/10/6/205 JMMP, Vol. 10, Pages 204: Development of a Launch Mechanism for Small Satellites Using Laser Powder Bed Fusion Process https://www.mdpi.com/2504-4494/10/6/204 The deployment of CubeSats requires reliable, lightweight, and space-efficient launch mechanisms. Traditional spring-based deployers often rely on standard off-the-shelf components, limiting the design flexibility. This study presents a pilot design-to-verification workflow for a CubeSat deployment mechanism manufactured by Laser Powder Bed Fusion from 316L stainless steel. The workflow integrates analytical sizing, kinematic and numerical force assessment, FEM-based LPBF process simulation employed as a design-support tool to predict thermal displacements and residual stress that occur during manufacturing, prototype manufacturing and optical inspection. Optical scanning indicated that the main envelope dimensions remained close to the nominal CAD values, while the support-plate warping was localized at the plate corners due to the residual thermal stress after the support removal. The study validates the manufacturability of a single LPBF orbital-deployer lunch mechanism and assesses its dimensional accuracy and workflow feasibility, rather than its functional mechanical performance. It also includes mitigation strategies for deployer distortions. 2026-06-11 JMMP, Vol. 10, Pages 204: Development of a Launch Mechanism for Small Satellites Using Laser Powder Bed Fusion Process

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060204

Authors: Cosmin Gogu Cătălin-Gheorghe Amza Cristina Pupăză

The deployment of CubeSats requires reliable, lightweight, and space-efficient launch mechanisms. Traditional spring-based deployers often rely on standard off-the-shelf components, limiting the design flexibility. This study presents a pilot design-to-verification workflow for a CubeSat deployment mechanism manufactured by Laser Powder Bed Fusion from 316L stainless steel. The workflow integrates analytical sizing, kinematic and numerical force assessment, FEM-based LPBF process simulation employed as a design-support tool to predict thermal displacements and residual stress that occur during manufacturing, prototype manufacturing and optical inspection. Optical scanning indicated that the main envelope dimensions remained close to the nominal CAD values, while the support-plate warping was localized at the plate corners due to the residual thermal stress after the support removal. The study validates the manufacturability of a single LPBF orbital-deployer lunch mechanism and assesses its dimensional accuracy and workflow feasibility, rather than its functional mechanical performance. It also includes mitigation strategies for deployer distortions.

]]> Development of a Launch Mechanism for Small Satellites Using Laser Powder Bed Fusion Process Cosmin Gogu Cătălin-Gheorghe Amza Cristina Pupăză doi: 10.3390/jmmp10060204 Journal of Manufacturing and Materials Processing 2026-06-11 Journal of Manufacturing and Materials Processing 2026-06-11 10 6 Article 204 10.3390/jmmp10060204 https://www.mdpi.com/2504-4494/10/6/204 JMMP, Vol. 10, Pages 203: Multi-Objective Optimization of a Composite FRP Laminated Sandwich Structure Using Artificial Neural Network and Particle Swarm Optimization Algorithm https://www.mdpi.com/2504-4494/10/6/203 Designing lightweight composite sandwich structures is challenging due to the conflicting objectives of minimizing structural weight and cost while satisfying strength and stiffness requirements. The optimization procedure becomes more complex when multiple discrete design variables and nonlinear material behavior are involved. This study presents a newly developed optimization methodology for a sandwich structure composed of Fiber Reinforced Polymer (FRP) laminated facesheets and an aluminum honeycomb core. To reduce the computational cost associated with repeated high-fidelity Finite Element (FE) analyses, a surrogate modeling strategy based on Artificial Neural Networks (ANNs) is employed to approximate the structural response. The applied dataset is generated using Monte Carlo simulation in which combinations of design variables are used as inputs, and the corresponding structural responses obtained from the analytical formulation are used as outputs for training the ANN surrogate model. The trained ANN model is integrated with a Multi-Objective Niching Memetic Particle Swarm Optimization (MO-NMPSO) algorithm to simultaneously minimize structural weight and material cost while satisfying constraints on facesheet strength, wrinkling, intra-cell buckling, deflection, core shear failure and structural thickness. The resulting Pareto-optimal solutions are validated through detailed FE simulations, demonstrating the reliability of the newly elaborated optimization framework. The results of the newly developed computationally efficient optimization procedure provide a diverse set of optimal design solutions for the investigated sandwich structure. 2026-06-11 JMMP, Vol. 10, Pages 203: Multi-Objective Optimization of a Composite FRP Laminated Sandwich Structure Using Artificial Neural Network and Particle Swarm Optimization Algorithm

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060203

Authors: Muhammad Ali Sadiq György Kovács

Designing lightweight composite sandwich structures is challenging due to the conflicting objectives of minimizing structural weight and cost while satisfying strength and stiffness requirements. The optimization procedure becomes more complex when multiple discrete design variables and nonlinear material behavior are involved. This study presents a newly developed optimization methodology for a sandwich structure composed of Fiber Reinforced Polymer (FRP) laminated facesheets and an aluminum honeycomb core. To reduce the computational cost associated with repeated high-fidelity Finite Element (FE) analyses, a surrogate modeling strategy based on Artificial Neural Networks (ANNs) is employed to approximate the structural response. The applied dataset is generated using Monte Carlo simulation in which combinations of design variables are used as inputs, and the corresponding structural responses obtained from the analytical formulation are used as outputs for training the ANN surrogate model. The trained ANN model is integrated with a Multi-Objective Niching Memetic Particle Swarm Optimization (MO-NMPSO) algorithm to simultaneously minimize structural weight and material cost while satisfying constraints on facesheet strength, wrinkling, intra-cell buckling, deflection, core shear failure and structural thickness. The resulting Pareto-optimal solutions are validated through detailed FE simulations, demonstrating the reliability of the newly elaborated optimization framework. The results of the newly developed computationally efficient optimization procedure provide a diverse set of optimal design solutions for the investigated sandwich structure.

]]> Multi-Objective Optimization of a Composite FRP Laminated Sandwich Structure Using Artificial Neural Network and Particle Swarm Optimization Algorithm Muhammad Ali Sadiq György Kovács doi: 10.3390/jmmp10060203 Journal of Manufacturing and Materials Processing 2026-06-11 Journal of Manufacturing and Materials Processing 2026-06-11 10 6 Article 203 10.3390/jmmp10060203 https://www.mdpi.com/2504-4494/10/6/203 JMMP, Vol. 10, Pages 202: Microstructural Diversity in Dispersed Composites Governed by Inclusion Distribution https://www.mdpi.com/2504-4494/10/6/202 The microstructure of metal matrix composites is inherently governed by fabrication routes and processing parameters, yet technological and physical constraints often prevent the realization of intended structural designs. In particle-reinforced composites produced via casting, interactions between the solidification front and inclusions frequently lead to agglomeration, segregation, and hence, a non-uniform distribution of the inclusions concentration. To mitigate these effects, post-processing techniques such as Friction Stir Processing offering particular promise for cast materials by refining microstructures and enhancing phase homogeneity. This study addresses these challenges by application of Fourier transform analysis to characterize stochastic inclusion distributions. Building on the Windows Washing method, we extend its application to heterogeneous media with varying inclusion concentrations. Through computer simulations and experimental analysis of real composites, we demonstrate that discrete Fourier transform can reveal hidden stochastic periodicity. The proposed framework provides a pathway toward improved predictive models and optimization strategies for metal matrix composites processing and performance. 2026-06-10 JMMP, Vol. 10, Pages 202: Microstructural Diversity in Dispersed Composites Governed by Inclusion Distribution

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060202

Authors: Vladimir Mityushev Pawel Kurtyka Zhanat Zhunussova Akylkerey Sarvarov

The microstructure of metal matrix composites is inherently governed by fabrication routes and processing parameters, yet technological and physical constraints often prevent the realization of intended structural designs. In particle-reinforced composites produced via casting, interactions between the solidification front and inclusions frequently lead to agglomeration, segregation, and hence, a non-uniform distribution of the inclusions concentration. To mitigate these effects, post-processing techniques such as Friction Stir Processing offering particular promise for cast materials by refining microstructures and enhancing phase homogeneity. This study addresses these challenges by application of Fourier transform analysis to characterize stochastic inclusion distributions. Building on the Windows Washing method, we extend its application to heterogeneous media with varying inclusion concentrations. Through computer simulations and experimental analysis of real composites, we demonstrate that discrete Fourier transform can reveal hidden stochastic periodicity. The proposed framework provides a pathway toward improved predictive models and optimization strategies for metal matrix composites processing and performance.

]]> Microstructural Diversity in Dispersed Composites Governed by Inclusion Distribution Vladimir Mityushev Pawel Kurtyka Zhanat Zhunussova Akylkerey Sarvarov doi: 10.3390/jmmp10060202 Journal of Manufacturing and Materials Processing 2026-06-10 Journal of Manufacturing and Materials Processing 2026-06-10 10 6 Article 202 10.3390/jmmp10060202 https://www.mdpi.com/2504-4494/10/6/202 JMMP, Vol. 10, Pages 201: Sustainable 3D Printing of Recycled PET: Influence of Infill Architecture and Layer Thickness on Mechanical Behavior https://www.mdpi.com/2504-4494/10/6/201 The utilization of polyethylene terephthalate (PET) waste from single-use packaging offers potential for sustainable manufacturing. This study evaluates recycled PET (rPET) from bottles as an FDM filament by varying infill architectures (honeycomb, gyroid, grid, and triangles) and layer thicknesses (0.20, 0.25, and 0.30 mm), with commercial PETG as a benchmark. Compared with previous rPET FDM studies, which were limited to reporting mechanical strength, the novelty of this study lies in the fact that it not only reports mechanical strength performance, but also compares printing time requirements and material efficiency. Efficiency calculations are obtained by comparing the weight of the filament to the weight of the printed specimen, which then correlates with optimizing processing time and costs. Overall, rPET produced densities of 1.11–1.22 g/cm3, tensile strengths of 12.5–22.5 MPa, flexural strengths of 12.5–30 MPa, impact strengths of 0.032–0.060 J/mm2, and surface roughnesses of Ra 5.2–7.1 μm, while PETG showed higher mechanical performance (tensile 30–39.5 MPa, flexural 30–50 MPa, impact 0.037–0.065 J/mm2) and comparable density (1.15–1.27 g/cm3). Within rPET, gyroid provided the best optimal performance; the gyroid (0.20 mm) variation achieved the highest impact response (0.060 J/mm2) and the lowest Ra (5.2 μm) and the gyroid (0.25 mm) variation maximized flexural strength (30 MPa) and the gyroid (0.30 mm) variation maximized tensile strength (22.5 MPa). Material utilization efficiency was consistently higher for rPET (65–68%) than for PETG (46–56%). These results provide an integrated rPET-specific assessment and practical parameter recommendations for functional 3D printing, while also aligning with SDG 12 by pro-moting resource-efficient circular-economy practices through the utilization of waste materials in additive manufacturing. 2026-06-08 JMMP, Vol. 10, Pages 201: Sustainable 3D Printing of Recycled PET: Influence of Infill Architecture and Layer Thickness on Mechanical Behavior

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060201

Authors: Rahmat Doni Widodo Muhammad Irfan Nuryanta Muhammad Akhsin Muflikhun

The utilization of polyethylene terephthalate (PET) waste from single-use packaging offers potential for sustainable manufacturing. This study evaluates recycled PET (rPET) from bottles as an FDM filament by varying infill architectures (honeycomb, gyroid, grid, and triangles) and layer thicknesses (0.20, 0.25, and 0.30 mm), with commercial PETG as a benchmark. Compared with previous rPET FDM studies, which were limited to reporting mechanical strength, the novelty of this study lies in the fact that it not only reports mechanical strength performance, but also compares printing time requirements and material efficiency. Efficiency calculations are obtained by comparing the weight of the filament to the weight of the printed specimen, which then correlates with optimizing processing time and costs. Overall, rPET produced densities of 1.11–1.22 g/cm3, tensile strengths of 12.5–22.5 MPa, flexural strengths of 12.5–30 MPa, impact strengths of 0.032–0.060 J/mm2, and surface roughnesses of Ra 5.2–7.1 μm, while PETG showed higher mechanical performance (tensile 30–39.5 MPa, flexural 30–50 MPa, impact 0.037–0.065 J/mm2) and comparable density (1.15–1.27 g/cm3). Within rPET, gyroid provided the best optimal performance; the gyroid (0.20 mm) variation achieved the highest impact response (0.060 J/mm2) and the lowest Ra (5.2 μm) and the gyroid (0.25 mm) variation maximized flexural strength (30 MPa) and the gyroid (0.30 mm) variation maximized tensile strength (22.5 MPa). Material utilization efficiency was consistently higher for rPET (65–68%) than for PETG (46–56%). These results provide an integrated rPET-specific assessment and practical parameter recommendations for functional 3D printing, while also aligning with SDG 12 by pro-moting resource-efficient circular-economy practices through the utilization of waste materials in additive manufacturing.

]]> Sustainable 3D Printing of Recycled PET: Influence of Infill Architecture and Layer Thickness on Mechanical Behavior Rahmat Doni Widodo Muhammad Irfan Nuryanta Muhammad Akhsin Muflikhun doi: 10.3390/jmmp10060201 Journal of Manufacturing and Materials Processing 2026-06-08 Journal of Manufacturing and Materials Processing 2026-06-08 10 6 Article 201 10.3390/jmmp10060201 https://www.mdpi.com/2504-4494/10/6/201 JMMP, Vol. 10, Pages 200: Roll Bonding of Aluminium Coupons Using the Established Fully Fledged Offline Fabrication Facilities https://www.mdpi.com/2504-4494/10/6/200 The South African aluminium industry faces technical challenges related to cladded ingots used in automotive heat exchangers, creating a need for offline processing methods that can replicate rolling processes like roll bonding, as large-scale industrial trials are costly and difficult to control. To address this, Mintek established a comprehensive offline manufacturing facility for process and product development of rolled metal products, focusing on the thermomechanical processing of aluminium alloys. In this study, stacked AA4045/AA3003mod coupons were processed under controlled conditions by varying thickness reduction, temperature, and reheating, aiming to investigate the effect of isothermal soaking time on microstructure and mechanical properties. Tensile tests were performed on clad sheets before and after brazing heat treatment, and fracture surfaces were examined via scanning electron microscopy. Samples heated at 505 °C for ≥38 h, followed by cold rolling and annealing, fell at the lower end of the 9031-H24 specification for yield strength, which is important for this application (i.e., the minimum tensile yield strength of 145 MPa and the ultimate tensile strength (UTS) range of 190 to 230 MPa). Fracture surface analysis revealed a dimple-dominated structure in cold-rolled and annealed samples, indicating ductile fracture. The study concludes that the offline roll-bonding method successfully replicates industrial cladding processes, and that isothermal soaking duration significantly influences mechanical performance, though careful control of thermal exposure is necessary to meet the specified mechanical properties. 2026-06-08 JMMP, Vol. 10, Pages 200: Roll Bonding of Aluminium Coupons Using the Established Fully Fledged Offline Fabrication Facilities

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060200

Authors: Joseph Moema Charles Siyasiya Veronica Morudu Maje Phasha Mbavhalelo Maumela

The South African aluminium industry faces technical challenges related to cladded ingots used in automotive heat exchangers, creating a need for offline processing methods that can replicate rolling processes like roll bonding, as large-scale industrial trials are costly and difficult to control. To address this, Mintek established a comprehensive offline manufacturing facility for process and product development of rolled metal products, focusing on the thermomechanical processing of aluminium alloys. In this study, stacked AA4045/AA3003mod coupons were processed under controlled conditions by varying thickness reduction, temperature, and reheating, aiming to investigate the effect of isothermal soaking time on microstructure and mechanical properties. Tensile tests were performed on clad sheets before and after brazing heat treatment, and fracture surfaces were examined via scanning electron microscopy. Samples heated at 505 °C for ≥38 h, followed by cold rolling and annealing, fell at the lower end of the 9031-H24 specification for yield strength, which is important for this application (i.e., the minimum tensile yield strength of 145 MPa and the ultimate tensile strength (UTS) range of 190 to 230 MPa). Fracture surface analysis revealed a dimple-dominated structure in cold-rolled and annealed samples, indicating ductile fracture. The study concludes that the offline roll-bonding method successfully replicates industrial cladding processes, and that isothermal soaking duration significantly influences mechanical performance, though careful control of thermal exposure is necessary to meet the specified mechanical properties.

]]> Roll Bonding of Aluminium Coupons Using the Established Fully Fledged Offline Fabrication Facilities Joseph Moema Charles Siyasiya Veronica Morudu Maje Phasha Mbavhalelo Maumela doi: 10.3390/jmmp10060200 Journal of Manufacturing and Materials Processing 2026-06-08 Journal of Manufacturing and Materials Processing 2026-06-08 10 6 Article 200 10.3390/jmmp10060200 https://www.mdpi.com/2504-4494/10/6/200 JMMP, Vol. 10, Pages 199: Mechanical and Thermal Performance of Sustainable PETG/Cork Composites Processed by Fused Filament Fabrication Technology https://www.mdpi.com/2504-4494/10/6/199 Despite major advances in polymer composites for Fused Filament Fabrication (FFF), designing environmentally sustainable materials from bio-based resources remains a key research priority. The objective of this study is to check the processability and properties of sustainable PETG/cork composites processed via FFF technology. Filaments with 5 and 10% of cork were created using a twin-screw extruder. Samples from these filaments were printed by FFF technology, and subsequently subjected to morphological, thermal and mechanical testing. As a result of the study, it was proved that the 3D-printing process did not result in a tensile strength decrease with an increasing cork percentage, as observed in mechanical testing of the filament. The addition of cork significantly increased plasticity without decreasing tensile strength when introducing 10% of cork particles. The interfacial temperatures of the prepared composites did not differ much from the polymer matrix and were 79.55 °C, 77.56 °C, 76.67 °C for PET-G, PET-G + 5% cork, and PET-G + 10% cork, respectively. Thermal conductivity decreased significantly as the percentage of cork increased. This work shows that FFF technology is one of the most suitable manufacturing options for PETG + 10% cork composites to produce things with low conductivity and the same thermal and mechanical properties as pure PETG. 2026-06-08 JMMP, Vol. 10, Pages 199: Mechanical and Thermal Performance of Sustainable PETG/Cork Composites Processed by Fused Filament Fabrication Technology

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060199

Authors: Saltanat Bergaliyeva Daniel Correro-Cabrera Ismael Romero-Ocaña Nuria Baladés Natalia Fernández Delgado Sergio I. Molina David L. Sales

Despite major advances in polymer composites for Fused Filament Fabrication (FFF), designing environmentally sustainable materials from bio-based resources remains a key research priority. The objective of this study is to check the processability and properties of sustainable PETG/cork composites processed via FFF technology. Filaments with 5 and 10% of cork were created using a twin-screw extruder. Samples from these filaments were printed by FFF technology, and subsequently subjected to morphological, thermal and mechanical testing. As a result of the study, it was proved that the 3D-printing process did not result in a tensile strength decrease with an increasing cork percentage, as observed in mechanical testing of the filament. The addition of cork significantly increased plasticity without decreasing tensile strength when introducing 10% of cork particles. The interfacial temperatures of the prepared composites did not differ much from the polymer matrix and were 79.55 °C, 77.56 °C, 76.67 °C for PET-G, PET-G + 5% cork, and PET-G + 10% cork, respectively. Thermal conductivity decreased significantly as the percentage of cork increased. This work shows that FFF technology is one of the most suitable manufacturing options for PETG + 10% cork composites to produce things with low conductivity and the same thermal and mechanical properties as pure PETG.

]]> Mechanical and Thermal Performance of Sustainable PETG/Cork Composites Processed by Fused Filament Fabrication Technology Saltanat Bergaliyeva Daniel Correro-Cabrera Ismael Romero-Ocaña Nuria Baladés Natalia Fernández Delgado Sergio I. Molina David L. Sales doi: 10.3390/jmmp10060199 Journal of Manufacturing and Materials Processing 2026-06-08 Journal of Manufacturing and Materials Processing 2026-06-08 10 6 Article 199 10.3390/jmmp10060199 https://www.mdpi.com/2504-4494/10/6/199 JMMP, Vol. 10, Pages 198: Manufacturing of 3D Auxetic Structures Through Perforations of Corrugated Systems https://www.mdpi.com/2504-4494/10/6/198 Fabrication of auxetic structures has always been a limiting factor in their availability. Their complex shape, a requirement originating from the deformation mechanism that leads to a negative Poisson’s ratio, has also limited their manufacturability. In the case of auxetic systems that deform through the rotating semi-rigid mechanism—which allows for the concurrent deformation and rotation of their constituent element—the situation is even more complicated. Relatively few examples of these types of structures are known, with most work on them being largely theoretical. This includes their use in explaining the auxetic mechanism in certain molecules. Nevertheless, these systems can, in principle, offer added functionalities, as they undergo a shape change while still exhibiting a negative Poisson’s ratio. To this end, this work presents a practical scheme for the manufacturing of 3D rotating semi-rigid units, whereby these are produced through perforations of corrugated sheets. For the purpose of this investigation, diamond-shaped perforations were chosen, and the side profile of the corrugated sheet consisted of successive semicircles that alternate in orientation. Analysis of the system indicated that a 3D negative Poisson’s ratio can be obtained while allowing the distance between the hinges to change during deformation. 2026-06-04 JMMP, Vol. 10, Pages 198: Manufacturing of 3D Auxetic Structures Through Perforations of Corrugated Systems

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060198

Authors: Libera Vitiello Gianluca Cicala Giovanni Filippone Pietro Russo Ruben Gatt Joseph N. Grima Pierre-Sandre Farrugia

Fabrication of auxetic structures has always been a limiting factor in their availability. Their complex shape, a requirement originating from the deformation mechanism that leads to a negative Poisson’s ratio, has also limited their manufacturability. In the case of auxetic systems that deform through the rotating semi-rigid mechanism—which allows for the concurrent deformation and rotation of their constituent element—the situation is even more complicated. Relatively few examples of these types of structures are known, with most work on them being largely theoretical. This includes their use in explaining the auxetic mechanism in certain molecules. Nevertheless, these systems can, in principle, offer added functionalities, as they undergo a shape change while still exhibiting a negative Poisson’s ratio. To this end, this work presents a practical scheme for the manufacturing of 3D rotating semi-rigid units, whereby these are produced through perforations of corrugated sheets. For the purpose of this investigation, diamond-shaped perforations were chosen, and the side profile of the corrugated sheet consisted of successive semicircles that alternate in orientation. Analysis of the system indicated that a 3D negative Poisson’s ratio can be obtained while allowing the distance between the hinges to change during deformation.

]]> Manufacturing of 3D Auxetic Structures Through Perforations of Corrugated Systems Libera Vitiello Gianluca Cicala Giovanni Filippone Pietro Russo Ruben Gatt Joseph N. Grima Pierre-Sandre Farrugia doi: 10.3390/jmmp10060198 Journal of Manufacturing and Materials Processing 2026-06-04 Journal of Manufacturing and Materials Processing 2026-06-04 10 6 Article 198 10.3390/jmmp10060198 https://www.mdpi.com/2504-4494/10/6/198 JMMP, Vol. 10, Pages 197: Design and Computational Efficiency of a GPU-Resident Integrated Execution Pipeline for Explicit Large-Deformation Finite Element Analysis https://www.mdpi.com/2504-4494/10/6/197 We describe a GPU-resident execution pipeline for explicit large-deformation finite element analysis in which every stage of the timestep—internal force evaluation, contact processing, nodal update, time integration, and minimum edge-length reduction—operates on arrays that remain in device memory, so per-step bulk transfers across PCIe are avoided. Contact is handled on the device through a shared-memory brute-force proximity search with warp-ballot stream compaction. We exercise the solver on a hemisphere compression benchmark at six mesh resolutions (83 K–1.89 M elements). On an NVIDIA L40, per-step speedups over a single CPU core range from about 99× to 138×, increasing with problem size and approaching a plateau near 137× for the largest meshes (above roughly 1 M elements); the contact-enabled configuration adds a net ON/OFF overhead of +13% to +21% to the step time. Against LS-DYNA running in SMP mode on the same problem, the proposed solver is roughly 94× faster than the best 8-core configuration, a margin consistent with the multicore saturation observed in the SMP measurements. The remaining limitations—single-GPU execution, FP32 arithmetic, and rigid-body contact search without a BVH broad phase—are identified as specific targets for multi-GPU, mixed-precision, and scalable-contact extensions. 2026-06-03 JMMP, Vol. 10, Pages 197: Design and Computational Efficiency of a GPU-Resident Integrated Execution Pipeline for Explicit Large-Deformation Finite Element Analysis

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060197

Authors: Honglae Kim Seokmoo Hong Naksoo Kim

We describe a GPU-resident execution pipeline for explicit large-deformation finite element analysis in which every stage of the timestep—internal force evaluation, contact processing, nodal update, time integration, and minimum edge-length reduction—operates on arrays that remain in device memory, so per-step bulk transfers across PCIe are avoided. Contact is handled on the device through a shared-memory brute-force proximity search with warp-ballot stream compaction. We exercise the solver on a hemisphere compression benchmark at six mesh resolutions (83 K–1.89 M elements). On an NVIDIA L40, per-step speedups over a single CPU core range from about 99× to 138×, increasing with problem size and approaching a plateau near 137× for the largest meshes (above roughly 1 M elements); the contact-enabled configuration adds a net ON/OFF overhead of +13% to +21% to the step time. Against LS-DYNA running in SMP mode on the same problem, the proposed solver is roughly 94× faster than the best 8-core configuration, a margin consistent with the multicore saturation observed in the SMP measurements. The remaining limitations—single-GPU execution, FP32 arithmetic, and rigid-body contact search without a BVH broad phase—are identified as specific targets for multi-GPU, mixed-precision, and scalable-contact extensions.

]]> Design and Computational Efficiency of a GPU-Resident Integrated Execution Pipeline for Explicit Large-Deformation Finite Element Analysis Honglae Kim Seokmoo Hong Naksoo Kim doi: 10.3390/jmmp10060197 Journal of Manufacturing and Materials Processing 2026-06-03 Journal of Manufacturing and Materials Processing 2026-06-03 10 6 Article 197 10.3390/jmmp10060197 https://www.mdpi.com/2504-4494/10/6/197 JMMP, Vol. 10, Pages 196: Synergistic Strengthening of Copper by In Situ Graphene Growth and Severe Plastic Deformation https://www.mdpi.com/2504-4494/10/6/196 High-purity copper features excellent electrical conductivity but generally low mechanical properties. Adding a three-dimensional graphene network as reinforcement to make a copper–graphene metal matrix composite is promising for a wide range of applications with better mechanical performance and functional capabilities. However, direct application in a metal matrix is difficult due to unfavorable wetting, which causes poor dispersion and weak interfacial bonding in the graphene–metal system. Here, the powder metallurgy method was used to construct a three-dimensional continuous graphene network in the copper matrix combined with high-pressure torsion. Optimized deformation/thermomechanical treatment enhanced the microstructural development processed by the severe plastic deformation method of high-pressure torsion. The primary advantage of this hybrid process is that it enables us to achieve grains with a size in the ultra-fine or even nanoscale. A homogeneous equiaxed nanostructure without segregation was observed during microstructural characterization, with a grain size of ~300 nm. This study investigated structural development during progressive deformation, and the samples were evaluated from the viewpoint of grain size and grain boundaries. The process significantly increased the microhardness of the copper–graphene composite. The tensile strength reached ~500 MPa at room temperature. The interpenetrating structural feature of graphene promoted interfacial shear stress to a high level, whereas plastic deformation increased the dislocation density and grain boundaries, thus resulting in significantly enhanced load transfer strengthening and crack-bridging toughness simultaneously. 2026-06-02 JMMP, Vol. 10, Pages 196: Synergistic Strengthening of Copper by In Situ Graphene Growth and Severe Plastic Deformation

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060196

Authors: Junaid Dar Laxman Bhatta Islam Hafez Megumi Kawasaki Dong Lin

High-purity copper features excellent electrical conductivity but generally low mechanical properties. Adding a three-dimensional graphene network as reinforcement to make a copper–graphene metal matrix composite is promising for a wide range of applications with better mechanical performance and functional capabilities. However, direct application in a metal matrix is difficult due to unfavorable wetting, which causes poor dispersion and weak interfacial bonding in the graphene–metal system. Here, the powder metallurgy method was used to construct a three-dimensional continuous graphene network in the copper matrix combined with high-pressure torsion. Optimized deformation/thermomechanical treatment enhanced the microstructural development processed by the severe plastic deformation method of high-pressure torsion. The primary advantage of this hybrid process is that it enables us to achieve grains with a size in the ultra-fine or even nanoscale. A homogeneous equiaxed nanostructure without segregation was observed during microstructural characterization, with a grain size of ~300 nm. This study investigated structural development during progressive deformation, and the samples were evaluated from the viewpoint of grain size and grain boundaries. The process significantly increased the microhardness of the copper–graphene composite. The tensile strength reached ~500 MPa at room temperature. The interpenetrating structural feature of graphene promoted interfacial shear stress to a high level, whereas plastic deformation increased the dislocation density and grain boundaries, thus resulting in significantly enhanced load transfer strengthening and crack-bridging toughness simultaneously.

]]> Synergistic Strengthening of Copper by In Situ Graphene Growth and Severe Plastic Deformation Junaid Dar Laxman Bhatta Islam Hafez Megumi Kawasaki Dong Lin doi: 10.3390/jmmp10060196 Journal of Manufacturing and Materials Processing 2026-06-02 Journal of Manufacturing and Materials Processing 2026-06-02 10 6 Article 196 10.3390/jmmp10060196 https://www.mdpi.com/2504-4494/10/6/196 JMMP, Vol. 10, Pages 195: An Overview of Plastic Deformation Preparation Methods and Application of Gradient-Structured Materials https://www.mdpi.com/2504-4494/10/6/195 Gradient-structured materials have attracted considerable attention due to their gradient microstructural distribution and the resulting unique mechanical properties, showing great potential in aerospace, marine, and energy applications. This review presents a comprehensive overview of plastic deformation methods for fabricating gradient-structured materials, according to the loading conditions and resulting deformation modes, which are categorized into localized loading-localized deformation, localized loading-localized/global deformation, and global loading-localized/global deformation strategies. The applications of gradient-structured materials are further summarized in terms of surface properties, bulk mechanical properties, and forming performance. Finally, the current challenges and future research directions are discussed, focusing on quantitative structure-property relationships for inverse design, efficient and scalable fabrication strategies, and the synergistic effects of multi-level microstructures. This review offers significant insights into plastic-deformation-based fabrication methods and the diverse application properties of gradient-structured materials. 2026-05-31 JMMP, Vol. 10, Pages 195: An Overview of Plastic Deformation Preparation Methods and Application of Gradient-Structured Materials

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060195

Authors: Zhenhai Xu Jiajia Wang Shaoxi Xue Debin Shan Jie Xu Bin Guo

Gradient-structured materials have attracted considerable attention due to their gradient microstructural distribution and the resulting unique mechanical properties, showing great potential in aerospace, marine, and energy applications. This review presents a comprehensive overview of plastic deformation methods for fabricating gradient-structured materials, according to the loading conditions and resulting deformation modes, which are categorized into localized loading-localized deformation, localized loading-localized/global deformation, and global loading-localized/global deformation strategies. The applications of gradient-structured materials are further summarized in terms of surface properties, bulk mechanical properties, and forming performance. Finally, the current challenges and future research directions are discussed, focusing on quantitative structure-property relationships for inverse design, efficient and scalable fabrication strategies, and the synergistic effects of multi-level microstructures. This review offers significant insights into plastic-deformation-based fabrication methods and the diverse application properties of gradient-structured materials.

]]> An Overview of Plastic Deformation Preparation Methods and Application of Gradient-Structured Materials Zhenhai Xu Jiajia Wang Shaoxi Xue Debin Shan Jie Xu Bin Guo doi: 10.3390/jmmp10060195 Journal of Manufacturing and Materials Processing 2026-05-31 Journal of Manufacturing and Materials Processing 2026-05-31 10 6 Review 195 10.3390/jmmp10060195 https://www.mdpi.com/2504-4494/10/6/195 JMMP, Vol. 10, Pages 194: A Numerical and Experimental Analysis of Large Interference Fitting Cylinders https://www.mdpi.com/2504-4494/10/6/194 This research analyses the mechanical behaviour of the insertion process between two cylinders that are commonly employed in non-rigid joints. Through comprehensive analysis, the study reveals the dynamics of insertion force, particularly by highlighting the impact of initial collisions on subsequent deformations and the ultimate evolution of insertion forces. Contrary to intuitive assumptions, our findings reveal that higher interference levels between cylinders do not uniformly correlate with increased maximum insertion force levels; instead, for certain cylinder combinations, higher interference generates lower maximum insertion force levels. Additionally, the significance of the thickness ratio as a pivotal determinant in predicting overall behaviour and insertion force, which is a variable that is often overlooked in conventional analyses, has been underscored. Furthermore, it has been demonstrated that the applicability of analytical equations that were developed as part of thick-walled cylinder theory diminishes when mechanical joints undergo plasticity, which underscores the need for alternative modelling approaches. Through finite element simulations, fidelity when representing insertion processes, with errors below 15%, not only capturing peak insertion forces but also delineating the nuanced evolution of forces and cylinder deformations, has been attained. Conversely, the analytical method employed from the examined literature yielded unrealistic insertion force estimations that proved inadequate for scenarios that involve substantial interference. 2026-05-31 JMMP, Vol. 10, Pages 194: A Numerical and Experimental Analysis of Large Interference Fitting Cylinders

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060194

Authors: Iñigo Llavori Alaitz Zabala Joseba Mendiguren Xuban Telleria Nagore Otegi Eneko Saenz-de-Argandoña

This research analyses the mechanical behaviour of the insertion process between two cylinders that are commonly employed in non-rigid joints. Through comprehensive analysis, the study reveals the dynamics of insertion force, particularly by highlighting the impact of initial collisions on subsequent deformations and the ultimate evolution of insertion forces. Contrary to intuitive assumptions, our findings reveal that higher interference levels between cylinders do not uniformly correlate with increased maximum insertion force levels; instead, for certain cylinder combinations, higher interference generates lower maximum insertion force levels. Additionally, the significance of the thickness ratio as a pivotal determinant in predicting overall behaviour and insertion force, which is a variable that is often overlooked in conventional analyses, has been underscored. Furthermore, it has been demonstrated that the applicability of analytical equations that were developed as part of thick-walled cylinder theory diminishes when mechanical joints undergo plasticity, which underscores the need for alternative modelling approaches. Through finite element simulations, fidelity when representing insertion processes, with errors below 15%, not only capturing peak insertion forces but also delineating the nuanced evolution of forces and cylinder deformations, has been attained. Conversely, the analytical method employed from the examined literature yielded unrealistic insertion force estimations that proved inadequate for scenarios that involve substantial interference.

]]> A Numerical and Experimental Analysis of Large Interference Fitting Cylinders Iñigo Llavori Alaitz Zabala Joseba Mendiguren Xuban Telleria Nagore Otegi Eneko Saenz-de-Argandoña doi: 10.3390/jmmp10060194 Journal of Manufacturing and Materials Processing 2026-05-31 Journal of Manufacturing and Materials Processing 2026-05-31 10 6 Article 194 10.3390/jmmp10060194 https://www.mdpi.com/2504-4494/10/6/194 JMMP, Vol. 10, Pages 193: Deep CNN-Based Multi-Class TIG Welding Defect Classification Using HDR Images with Explainable AI https://www.mdpi.com/2504-4494/10/6/193 Recent advances in deep convolutional neural networks (D-CNNs) have improved automated welding defect inspection. This study presents an explainable comparative framework for multi-class classification of defects in Aluminium 5083 TIG weld joints using High Dynamic Range (HDR) image data, integrating a transfer-learning model, stratified five-fold cross-validation, computational-time analysis, and Grad-CAM-based visual interpretation. Five transfer-learning-based D-CNN architectures such as VGG16, VGG19, Inception V3, MobileNet, and DenseNet were trained, validated, and tested under a common evaluation protocol to assess their suitability for welding defect classification. The dataset was organised into classes such as good weld, contamination, lack of fusion, lack of penetration, and misalignment. Model performance was compared using multiple evaluation metrics. Stratified five-fold cross-validation was also performed to assess model stability. Alongside the cross-validation, training/inference times were also recorded to evaluate computational feasibility. Grad-CAM was used as an explainable artificial intelligence (XAI) technique in order to provide visual interpretation of weld regions. Among evaluated models, DenseNet achieved the best overall performance, with a classification accuracy of 98%, and showed the least confusion across defect classes. The Grad-CAM visualisations showed that the model focused on defect-relevant weld regions, demonstrating that transfer-learning D-CNNs with XAI can support TIG welding defect classification and effective visual quality assessment. 2026-05-30 JMMP, Vol. 10, Pages 193: Deep CNN-Based Multi-Class TIG Welding Defect Classification Using HDR Images with Explainable AI

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060193

Authors: Deepika Nikam Sagar Nikam Tejaswini Bhosale Declan Harkin Mayur Sawant Cormac McGarrigle

Recent advances in deep convolutional neural networks (D-CNNs) have improved automated welding defect inspection. This study presents an explainable comparative framework for multi-class classification of defects in Aluminium 5083 TIG weld joints using High Dynamic Range (HDR) image data, integrating a transfer-learning model, stratified five-fold cross-validation, computational-time analysis, and Grad-CAM-based visual interpretation. Five transfer-learning-based D-CNN architectures such as VGG16, VGG19, Inception V3, MobileNet, and DenseNet were trained, validated, and tested under a common evaluation protocol to assess their suitability for welding defect classification. The dataset was organised into classes such as good weld, contamination, lack of fusion, lack of penetration, and misalignment. Model performance was compared using multiple evaluation metrics. Stratified five-fold cross-validation was also performed to assess model stability. Alongside the cross-validation, training/inference times were also recorded to evaluate computational feasibility. Grad-CAM was used as an explainable artificial intelligence (XAI) technique in order to provide visual interpretation of weld regions. Among evaluated models, DenseNet achieved the best overall performance, with a classification accuracy of 98%, and showed the least confusion across defect classes. The Grad-CAM visualisations showed that the model focused on defect-relevant weld regions, demonstrating that transfer-learning D-CNNs with XAI can support TIG welding defect classification and effective visual quality assessment.

]]> Deep CNN-Based Multi-Class TIG Welding Defect Classification Using HDR Images with Explainable AI Deepika Nikam Sagar Nikam Tejaswini Bhosale Declan Harkin Mayur Sawant Cormac McGarrigle doi: 10.3390/jmmp10060193 Journal of Manufacturing and Materials Processing 2026-05-30 Journal of Manufacturing and Materials Processing 2026-05-30 10 6 Article 193 10.3390/jmmp10060193 https://www.mdpi.com/2504-4494/10/6/193 JMMP, Vol. 10, Pages 192: Comparative Life Cycle Assessment of Hull Manufacturing for Small-Size Crafts https://www.mdpi.com/2504-4494/10/6/192 In recent years, environmental sustainability has become a key issue in the shipbuilding industry, driving research towards a reduction in the environmental impact throughout the entire life cycle of vessels. In this context, composite materials are a solid alternative to achieve mechanical performance optimization and energy consumption reduction. This study compares two hull configurations, one in a glass fiber-reinforced thermoset composite and one in a thermoplastic composite sandwich structure, through life cycle assessment. The aim is to assess the influence of material choice and structural configuration on overall environmental impacts by analyzing energy and material inputs and emissions throughout the entire life cycle, from “cradle to grave” excluding the end-of-life treatment. The results evidence a 36% average reduction in the impact categories analyzed. Moreover, economic benefits emerged, with a 35% reduction in the cost of energy required during the analyzed life cycle phases and 9% reduction in the material supply. This work aims to contribute to the definition of more sustainable design strategies to produce hulls and naval components, promoting a transition towards a more efficient and environmentally friendly nautical sector. 2026-05-30 JMMP, Vol. 10, Pages 192: Comparative Life Cycle Assessment of Hull Manufacturing for Small-Size Crafts

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060192

Authors: Paolo De Sio Vittorio Rosanova Vitantonio Esperto Antonello Astarita Fausto Tucci

In recent years, environmental sustainability has become a key issue in the shipbuilding industry, driving research towards a reduction in the environmental impact throughout the entire life cycle of vessels. In this context, composite materials are a solid alternative to achieve mechanical performance optimization and energy consumption reduction. This study compares two hull configurations, one in a glass fiber-reinforced thermoset composite and one in a thermoplastic composite sandwich structure, through life cycle assessment. The aim is to assess the influence of material choice and structural configuration on overall environmental impacts by analyzing energy and material inputs and emissions throughout the entire life cycle, from “cradle to grave” excluding the end-of-life treatment. The results evidence a 36% average reduction in the impact categories analyzed. Moreover, economic benefits emerged, with a 35% reduction in the cost of energy required during the analyzed life cycle phases and 9% reduction in the material supply. This work aims to contribute to the definition of more sustainable design strategies to produce hulls and naval components, promoting a transition towards a more efficient and environmentally friendly nautical sector.

]]> Comparative Life Cycle Assessment of Hull Manufacturing for Small-Size Crafts Paolo De Sio Vittorio Rosanova Vitantonio Esperto Antonello Astarita Fausto Tucci doi: 10.3390/jmmp10060192 Journal of Manufacturing and Materials Processing 2026-05-30 Journal of Manufacturing and Materials Processing 2026-05-30 10 6 Article 192 10.3390/jmmp10060192 https://www.mdpi.com/2504-4494/10/6/192 JMMP, Vol. 10, Pages 191: Machining-Induced Surface Deformation Layer and the Impact on Tensile Plasticity of 316L Stainless Steel https://www.mdpi.com/2504-4494/10/6/191 316L stainless steel is widely used in aerospace components because of its mechanical properties and corrosion resistance. Standard tensile specimens are commonly used to evaluate material behavior, yet their measured tensile response can be affected by the final turning process. This study investigated the effects of cutting speed and depth of cut on the surface integrity and tensile properties of small standard 316L tensile specimens. Cutting-temperature measurement, optical surface characterization, EBSD analysis, fracture observation, and quasi-static tensile testing were combined to evaluate the machined specimens. A cutting speed of 45 m/min produced the most stable thermal response after repeated tool–workpiece contacts, with a temperature variation of 40.3%. Lower cutting speeds suppressed vibration-induced micro-pits and improved the morphology consistency between Area I and Area II. At the maximum depth of cut, increasing the cutting speed from 15 m/min to 60 m/min reduced the tensile strength from 1136.02 MPa to 1082.75 MPa and the tensile elongation from 56.6% to 53.5%. These results show that the tensile properties of turned specimens are governed by the combined effects of thermal response, surface morphology, deformation-layer microstructure, and fracture behavior. Among the tested conditions, Vc = 15 m/min, ap = 0.4 mm, and f = 0.1 mm/rev are recommended when tensile properties are the main requirement. 2026-05-29 JMMP, Vol. 10, Pages 191: Machining-Induced Surface Deformation Layer and the Impact on Tensile Plasticity of 316L Stainless Steel

Journal of Manufacturing and Materials Processing doi: 10.3390/jmmp10060191

Authors: Bokai Lou Jing Ni Jinghui Zhou Lihua He Zhenbing Cai Zefei Zhu

316L stainless steel is widely used in aerospace components because of its mechanical properties and corrosion resistance. Standard tensile specimens are commonly used to evaluate material behavior, yet their measured tensile response can be affected by the final turning process. This study investigated the effects of cutting speed and depth of cut on the surface integrity and tensile properties of small standard 316L tensile specimens. Cutting-temperature measurement, optical surface characterization, EBSD analysis, fracture observation, and quasi-static tensile testing were combined to evaluate the machined specimens. A cutting speed of 45 m/min produced the most stable thermal response after repeated tool–workpiece contacts, with a temperature variation of 40.3%. Lower cutting speeds suppressed vibration-induced micro-pits and improved the morphology consistency between Area I and Area II. At the maximum depth of cut, increasing the cutting speed from 15 m/min to 60 m/min reduced the tensile strength from 1136.02 MPa to 1082.75 MPa and the tensile elongation from 56.6% to 53.5%. These results show that the tensile properties of turned specimens are governed by the combined effects of thermal response, surface morphology, deformation-layer microstructure, and fracture behavior. Among the tested conditions, Vc = 15 m/min, ap = 0.4 mm, and f = 0.1 mm/rev are recommended when tensile properties are the main requirement.

]]> Machining-Induced Surface Deformation Layer and the Impact on Tensile Plasticity of 316L Stainless Steel Bokai Lou Jing Ni Jinghui Zhou Lihua He Zhenbing Cai Zefei Zhu doi: 10.3390/jmmp10060191 Journal of Manufacturing and Materials Processing 2026-05-29 Journal of Manufacturing and Materials Processing 2026-05-29 10 6 Article 191 10.3390/jmmp10060191 https://www.mdpi.com/2504-4494/10/6/191