Journal of Manufacturing and Materials Processing

Over the past 20 years, laser beam–electric arc hybrid welding has gained popularity, enabling high quality and efficiency standards needed for steel welds in structures subjected to severe working conditions. This process enables single-pass welding of thick components, overcoming issues concerning the individual use of traditional processes based on an electric arc or laser beam. Therefore, thorough knowledge of both processes is necessary to combine them optimally in terms of efficiency, reduced presence of defects, corrosion resistance, and mechanical and metallurgical features of the welds. This article aims to review the technical and metallurgical aspects of hybrid welding reported in the scientific literature mainly of the last decade, outlining possible choices for system configuration, the inter-distance between the two heat sources, as well as the key process parameters, considering their effects on the weld characteristics and also taking into account the consequences for solidification modes and weld composition. Finally, a specific section has been reserved for hybrid welding of clad steel plates. Full article

Aluminium alloy 6082 is widely used in the automotive and aerospace industries due to its high strength-to-weight ratio. However, its structural integrity can sometimes be affected by an early fatigue failure. This study investigates the fatigue performance of extruded 6082-T6 samples through a series of fatigue tests conducted at varying stress levels. The material showed significant variability under identical fatigue conditions, suggesting the presence of microstructural defects. Scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) and scanning transmission electron microscopy (S/TEM) were used to identify the nature and location of the defects and evaluate the underlying mechanisms influencing the fatigue performance. Computer tomography (CT) also confirmed the presence of oxide inclusions on the fracture surface and near the edges of the samples. These oxide inclusions are distributed throughout the material heterogeneously and in the form of broken oxide films, suggesting that they might have originated during the material’s early processing stages. These oxides acted as stress concentrators, initiating microcracks that led to catastrophic and unpredictable early failure, ultimately reducing the fatigue life of micro-oxide-containing samples. These results highlight the need for better casting control and improved post-processing techniques to minimise the effect of oxide presence in the final components, thus enhancing their fatigue life. Full article

This paper presents optimization of peak temperatures achieved during friction stir welding (FSW) of Al-6061-T6 alloys. This research work employed a novel approach by investigating the effect of FSW welding process parameters on peak temperatures through the implementation of finite element analysis (FEA), the Taguchi method, analysis of variance (ANOVA), and machine learning (ML) algorithms. COMSOL 6.0 Multiphysics was used to perform FEA to predict peak temperatures, incorporating seven distinctive welding parameters: tool material, pin diameter, shoulder diameter, tool rotational speed, welding speed, axial force, and coefficient of friction. The influence of these parameters was investigated using an L32 Taguchi array and analysis of variance (ANOVA), revealing that axial force and tool rotational speed were the most significant parameters affecting peak temperatures. Some simulations showed temperatures exceeding the material’s melting point, indicating the need for improved thermal control. This was achieved by using three machine learning (ML) algorithms, i.e., Logistic Regression, k-Nearest Neighbors (k-NN), and Naive Bayes. A dataset of 324 data points was prepared using a factorial design to implement these algorithms. These algorithms predicted the welding conditions where the temperature exceeded the melting temperature of Al-6061-T6. It was found that the Logistic Regression classifier demonstrated the highest performance, achieving an accuracy of 98.14% as compared to Naive Bayes and k-NN classifiers. These findings contribute to sustainable welding practices by minimizing excessive heat generation, preserving material properties, and enhancing weld quality. Full article

This study investigates the influence of die design parameters on forging forces and thermomechanical responses during near-solidus forging (NSF) of complex steel components. Finite element simulations using Forge NxT analyzed six die configurations varying geometry orientation, gating system design (conical, cylindrical, curvilinear), and draft angles (20° and 30°), with 42CrMo4E steel modeled at 1360 °C. Key responses including punch and lateral forces, temperature distribution, strain localization, and die stress were evaluated to assess design effects. Results showed that the gating system geometry critically controls material flow and load requirements. The conical gating design with a 30° draft angle yielded the lowest punch (141.54 t) and lateral (149.44 t) forces, alongside uniform temperature and strain distributions, which improve product quality by minimizing defects and incomplete filling. Lower lateral forces also reduce die opening risk, enhancing die life. In contrast, the base case with a 20° draft angle exhibited higher forces and uneven strain, increasing die stress and compromising part quality. These findings highlight the importance of selecting appropriate gating systems and draft angles to reduce forming loads, increase die life, and improve uniform material flow, contributing to better understanding of die design in NSF of complex steel components. Full article

The Scalable and Expeditious Additive Manufacturing (SEAM) process is an advanced additive manufacturing (AM) technique that relies on the optimization of metal powder suspensions to achieve high-quality 3D-printed components. This study explores the critical role of dispersants in enhancing the performance of stainless steel (SS) 420 metal powder suspensions for the SEAM process by improving powder loading, recyclability, flowability, and consequent final part density. The addition of dispersant allows for increased powder contents while preserving stable rheological properties, thereby enabling higher powder loading without compromising the rheological characteristics required in the SEAM process. Previously, our team implemented a two-step printing strategy to address the segregation issues during printing. Nonetheless, the semi-cured layer was not recyclable after printing, resulting in a significant amount of waste in the SEAM process. This, in turn, leads to a considerable increase in material costs. On the other hand, the addition of a dispersant has been shown to enhance suspension stability, enabling multiple cycles of reuse. This novel approach has been demonstrated to reduce material waste and lower production costs. The enhanced flowability guarantees uniform suspension spreading, resulting in defect-free layer deposition and superior process control. Moreover, the dispersant’s ability to impede particle agglomeration and promote powder loading contributes to the attainment of a 99.33% relative density in the final sintered SS420 parts, thereby markedly enhancing their mechanical integrity. These findings demonstrate the pivotal role of dispersants in refining the SEAM process, enabling the production of high-density, cost-effective metal components with superior material utilization and process efficiency. Full article

Resin Transfer Molding (RTM) is a widely used composite manufacturing process where liquid resin is injected into a closed mold filled with a fibrous preform. By applying this process, large pieces with complex shapes can be produced on an industrial scale, presenting excellent properties and quality. A true physical phenomenon occurring in the RTM process, especially when using vegetable fibers, is related to the absorption of resin by the fiber during the infiltration process. The real effect is related to the slowdown in the advance of the fluid flow front, increasing the mold filling time. This phenomenon is little explored in the literature, especially for non-isothermal conditions. In this sense, this paper does a numerical study of the liquid injection process in a closed and heated mold. The proposed mathematical modeling considers the radial, three-dimensional, and transient flow, variable injection pressure, and fluid viscosity, including the effect of liquid fluid absorption by the reinforcement (fiber). Simulations were carried out using Computational Fluid Dynamic tools. The numerical results of the filling time were compared with experimental results, and a good approximation was obtained. Further, the pressure, temperature, velocity, and volumetric fraction fields, as well as the transient history of the fluid front position and injection fluid volumetric flow rate, are presented and analyzed. Full article

In this study, prospects of designing new Al–Ca–Cu–Mn (Zr) alloys for additive manufacturing (AM) were evaluated for the example of laser remelting of thin-sheet rolled products. The new as-cast alloys have a hypereutectic structure containing Al₂₇Ca₃Cu₇ primary crystals and ultrafine eutectic particles of (Al,Cu)₄Ca and Al₂₇Ca₃Cu₇ phases in equilibrium with the aluminum solid solution. The solid solutions are additionally strengthened by alloying with Mn and micro additions of Zr, which contribute to the formation of coarsening-resistant phases without compromising the manufacturability of the alloys. Laser remelting, which simulates AM-typical solidification conditions, promotes the formation of a pseudoeutectic cellular structure without the occurrence of undesirable primary Al₂₇Ca₃Cu₇. The size of the dendritic cells and eutectic particles is 10 times smaller (for solidification rates of ~200 K/s) than that of the as-cast state. This structure provides for a higher hardness of the laser-remelted alloy (96 HV) as compared to the as-cast alloy (85 HV). Data for the alloy after 350–400 °C long-term annealing for up to 100 h show that the hardness of the Al–Ca–Cu–Mn–Zr alloys declines relatively slowly by ~7.5% as compared to the Zr-free alloy, whose hardness decreases by ~22%. Thus, one can consider these alloys as a promising candidate for AM processes that require high thermal stability. Full article

Frictional conditions at the workpiece–die interface are critical in metal forming, as significant plastic deformation generates heat that affects lubricant performance. Understanding lubricant behavior, especially its influence on friction under elevated temperatures, is essential for optimizing forming processes and meeting ecological demands. While the conventional ring compression test evaluates friction through inner diameter changes, it becomes unreliable when friction is transient. In this study, a warm ring compression test incorporating an in situ measurement system is proposed to evaluate the transient frictional behavior of lubricants under temperature rise due to plastic deformation. Results show that at T = 50 °C and 150 °C, the friction coefficient increases notably with the compression ratio, whereas at T = 100 °C, it remains relatively stable. This stability is likely due to the optimal performance of the chlorinated base lubricant at 100 °C, where boundary lubrication is most effective. At T = 50 °C, the additive activation is insufficient, and at T = 150 °C, thermal degradation may reduce its effectiveness. Finite element simulations using the transient friction coefficient reproduce the deformed ring cross-section with high accuracy, while those using constant friction values show less agreement. Full article

This study examines the capabilities and optimisation of electrochemical jet machining (ECJM), a component of the electrochemical machining (ECM) production chain. A localised electrolyte jet helps remove material from selective areas; it is a suitable process for contoured parts and hard-to-machine material without inflicting thermal or mechanical stresses. In this regard, the study incorporates details of an experimental layout and variation in parameters in terms of voltage, electrolyte concentration, and jet velocity. The most striking findings indicate that the material removal rate and surface quality are susceptible to parameters such as applied voltage and stand-off distance, and electrolyte concentration and jet velocity (via electrolyte supply rate) fixed. Higher voltages and fixed electrolyte concentrations give higher removal rates, though this might impair the surface finish, thereby requiring a trade-off at best. These results provide insights into optimising process parameters for enhanced precision and efficiency in ECJM. Future research could focus on advanced electrolytes and improving scalability for industrial applications. Full article

In the present study, an L-shaped multi-walled structure of NiTi shape memory alloy (SMA) was fabricated by using the wire arc additive manufacturing (WAAM) method on a titanium substrate. The present study aims to investigate the fabricated structure for microstructure, macrostructure, and mechanical properties. The 40 layers of L-shaped structure were successfully fabricated at optimized parameters of wire feed speed at 6 m/min, travel speed at 12 mm/s, and voltage at 20 V. The macrographs demonstrated the continuous bonding among the layers with complete fusion. The microstructure in the area between the two middle layers has exhibited a mixture of columnar grains (both coarse and fine), interspersed with dendritic colonies. The microstructure in the topmost layers has exhibited finer colonial structures in relatively greater numbers. The microhardness (MH) test has shown the average values of 283.2 ± 3.67 HV and 371.1 ± 5.81 HV at the bottom and topmost layers, respectively. A tensile test was conducted for specimens extracted from deposition and build directions, which showed consistent mechanical behavior. For the deposition direction, the average ultimate tensile strength (UTS) and elongation (EL) were obtained as 831 ± 22.91 MPa and 14.32 ± 0.55%, respectively, while the build direction has shown average UTS and EL values of 774 ± 6.56 MPa and 14.16 ± 0.21%, respectively. The elongation exceeding 10% in all samples suggests that the fabricated structure demonstrates properties comparable to those of wrought metal. Fractography of all tensile specimens has shown good ductility and toughness. Lastly, a differential scanning calorimetry test was carried out to assess the retention of shape memory effect for the fabricated structure. The authors believe that the findings of this work will be valuable for various industrial applications. Full article

This paper presents three realizations of a complete set with a horn antenna and a focusing Gradient Index (GRIN) lens in X-band. The set was specifically designed for advancing additive manufacturing (AM) of polymers with different materials and techniques. The set has three constituent parts: a horn antenna, a support, and a lens. The horn antenna is the active element and must be electrically conductive; it was manufactured with Rigid10K acrylic resin and subsequently metallized using an electroless process. The support needed to be light, robust, and electrically transparent, so that Polyamide 11 (PA11) was used. The lens realization was intended for a dielectric material whose permittivity varies with its density. Therefore, the dielectric permittivity and loss tangent of different polymeric materials used in AM at 2.45, 6.25, and 24.5 GHz were measured. In addition, stochastic and gyroid mesh structures have been studied. These structures allow for printing a volume that presents porosity, enabling control over material density. Measuring the dielectric characteristics of each material with each density enables the establishment of graphs that relate them. The sets were then manufactured, and their frequency response and radiation diagram were measured, showing excellent results when compared with the literature. Full article

The future of the automotive industry appears to hinge on the integration of dissimilar materials, such as aluminum alloys and carbon steel. However, this combination can lead to galvanic corrosion, compromising the structural integrity. In this study, laser-welded joints of 6013-T4 aluminum alloy and DP980 steel were evaluated for their morphology, microhardness, and corrosion resistance. Corrosion resistance was assessed using the electrochemical noise technique over time in 0.1 M Na₂SO₄ and 3.5% NaCl solutions. The wavelet function was applied to remove the DC trend, and energy diagrams were generated to identify the type of corrosive process occurring on the electrodes. Corrosion on the electrodes was also monitored using photomicrographic images. Analysis revealed an aluminum–steel mixture in the melting zone, along with the presence of AlFe, AlFe₃, and AlI₃Fe₄ intermetallic compounds. The highest Vickers microhardness was observed in the heat-affected zone, adjacent to the melt zone, where a martensitic microstructure was identified. The 6013-T4 aluminum alloy demonstrated the highest corrosion resistance in both media. Conversely, the electrochemical noise resistance was similar for the DP980 steel and the weld bead, indicating that the laser welding process does not significantly impact this property. The energy diagrams showed that localized pitting corrosion was the predominant form of corrosion. However, generalized and mixed corrosion were also observed, which corroborated the macroscopic analysis of the electrodes. Full article

Injection molding is a fundamental process for transforming plastics into various industrial components. Among the critical aspects studied in this process, volumetric contraction and warpage of plastic parts are of particular importance. Achieving precise control over warpage is crucial for ensuring the production of high-quality components. This research explores optimizing injection process parameters to minimize volumetric contraction and warpage in rectangular polypropylene (PP) parts. The study employs experimental analysis, MoldFlow simulation, and Artificial Neural Network (ANN) modeling. MoldFlow simulation software provides valuable data on warpage, serving as input for the ANN model. Based on the Backpropagation Neural Network algorithm, the optimized ANN model accurately predicts warpage by considering factors such as part thickness, flow path distance, and flow path tangent. The study highlights the importance of accurately setting injection parameters to achieve optimal warpage results. The BPNN-based approach offers a faster and more efficient alternative to computer-aided engineering (CAE) processes for studying warpage. Full article

With the growing need for lightweight, durable, and high-performance structures, additively manufactured (AM) polymer composite structures have captured significant attention in the engineering community. These structures offer considerable advantages in various dynamic engineering sectors including automotive, aviation, and military. Thus, this investigation emphasizes the numerical analysis of the dynamic properties and vibration control of AM polylactic acid (PLA) composite structures reinforced with continuous glass fibers (CGFR-PLA) and carbon fibers (CCFR-PLA), with 0°–0° and 0°–90° layer orientations. The findings of this numerical study are compared and validated against earlier published experimental results. Initially, the numerical models were created using the Abaqus CAE 2024, replicating the actual experimental models. The numerical bending modal frequency of each numerical model is determined, and the 0°–0° oriented models exhibited considerably higher values compared to the corresponding 0°–90° models. Significant differences were noted between the numerical and experimental values in the higher modes, mainly due to existence of voids and misalignment in the actual models that were not considered in numerical models. Following this, a numerical amplitude frequency response (AFR) analysis was conducted to observe vibration amplitude variations as a function of frequency. The AFR numerical results demonstrated consistent trends with the experimental results despite differences between the absolute values of both scenarios. Afterwards, vibration amplitude control analysis was performed under the influence of a macro fiber composite (MFC) actuator. The findings from both numerical and experimental cases revealed that vibration control was noticeably higher in 0°–0° oriented structures compared to 0°–90° structures. Experimental models demonstrated higher vibration control effectiveness than the corresponding numerical models. Although significant differences between the numerical and experimental vibration response values were observed in each composite structure, the numerical results exhibited consistent trends with the experiments. This discrepancy is attributed to the challenge of capturing all boundary conditions of the experimental scenario and incorporating them into the numerical simulation. Full article

In recent decades, the automotive industry has faced challenges around improving energy efficiency, reducing pollutant emissions, increasing occupant safety, and reducing production costs. To solve these challenges, it is necessary to reduce the weight of vehicle bodies. In this way, the steel industry has developed more efficient metal alloys. To combine vehicle mass reduction with improved performance in deformations in cases of impact, a new family of advanced steels is present, AHSS (Advanced High-Strength Steels). However, this family of steels has lower formability and greater springback compared to conventional steels; if it is not properly controlled, it will directly affect the accuracy of the product and its quality. Different regions of a stamped component, such as the flange, the body wall, and the punch pole, are subjected to different states of stress and deformation, determined by numerous process variables, such as friction/lubrication and tool geometry, in addition to blank holder force and drawbead geometry, which induce the material to different deformation modes. Thus, it is understood that the degree of work hardening in each of these regions can be evaluated by grain morphology and material hardening, defining critical regions of embrittlement that, consequently, will affect the material’s stampability. This work aims to study the formability of the cold-formed DP600 steel sheets in the die radius region using a Modified Nakazima test, varying drawbead geometry, followed by a nanohardness evaluation and material characterization through the electron backscatter diffraction (EBSD). The main objective is to analyze the work hardening in the critical blank regions by applying these techniques. The nanoindentation evaluations were consistent in die radius and demonstrated the hardening influence, proving that the circular drawbead presented the most uniform hardness variation along the profile of the stamped blank and presented lower hardness values in relation to the other geometries, concluding that the drawbead attenuates this variation, contributing to better sheet formability, which corroborates the Forming Limit Curve results. Full article

The extensive use of copper in thermal and electrical systems calls for constant performance enhancement by means of innovative material treatments. The effects on the microstructural, mechanical, and electrical characteristics of copper in deep cryogenic treatment (DCT) and deep cryogenic treatment followed by heat treatment (DCT + HT) are investigated in this work. Copper samples were treated for various soaking durations ranging from 6 to 24 h. Mechanical properties such as tensile strength, hardness, and wear rate were analyzed. In the DCT-treated samples, tensile strength increased, reaching a peak of 343 MPa at 18 h, alongside increased hardness (128 HV) and a refined grain size of 9.58 µm, primarily due to elevated dislocation density and microstrain. At 18 h of soaking, DCT + HT resulted in improved structural stability, high hardness (149 HV), a fine grain size (7.42 µm), and the lowest wear rate (7.73 × 10⁻¹⁰ mm³/Nm), consistent with Hall–Petch strengthening. Electrical measurements revealed improved electron mobility (52.08 cm²/V·s) for samples soaked for 24 h in DCT + HT, attributed to increased crystallite size (39.9 nm), reduced lattice strain, and higher (111) texture intensity. SEM–EBSD analysis showed a substantial increase in low-angle grain boundaries (LAGBs) in DCT + HT-treated samples, correlating with enhanced electrical conductivity. Overall, an 18 h soaking duration was found to be optimal for both treatments. However, the strengthening mechanism in DCT + HT is influenced by grain boundary stabilization and thermal recovery and is different to DCT, which is strain-induced enhancement. Full article

The research presented herein investigates the impact of axial force and feed rate in the Friction Stir Welding (FSW) of aluminum alloy 6061-T6 in a GROB G552 horizontal 5-axis CNC machine with adaptive torque control enabled. The purpose of this study is to further advance the performance and characteristics of FSW aluminum alloys in 5-axis CNCs, particularly in conjunction with adaptive torque control. The Taguchi and ANOVA methods were utilized to define parameter tables and analyze the resulting data. Optical microscopy and tensile tests were performed on the welded samples to evaluate weld quality. The results from this study provide clear evidence that axial force has a significant effect on tensile strength in FSW AA6061-T6. The maximum UTS found in this study, welded with an axial force of 9.4 kN, retained 69% tensile strength of the base material. Conversely, a decrease in strength and an increase in void formation was found at higher feed rates with this force. Ideal welds, with minimal defects across all feed rates, were performed with an axial force of 8.3 kN. A feed rate of 300 mm/min at this force resulted in a 67% base metal strength. These findings contribute to improving joint strength and application efficiency in FSW AA6061-T6 performed in a horizontal 5-axis CNC machine where adaptive torque control is enabled. Full article

The present study introduces an AI (Artificial Intelligence) framework for surface roughness assessment in milling operations through sound signal processing. As industrial demands escalate for in-process quality control solutions, the proposed system leverages audio data to estimate surface finish states without interrupting production. In order to address this, a novel classification approach was developed that maps audio waveform data into predictive indicators of surface quality. In particular, an experimental dataset was employed consisting of sound signals that were captured during milling procedures applying various machining conditions, where each signal was labeled with a corresponding roughness quality obtained via offline metrology. The formulated classification pipeline commences with audio acquisition, resampling, and normalization to ensure consistency across the dataset. These signals are then transformed into Mel-Frequency Cepstral Coefficients (MFCCs), which yield a compact time–frequency representation optimized for human auditory perception. Next, several AI algorithms were trained in order to classify these MFCCs into predefined surface roughness categories. Finally, the results of the work demonstrate that sound signals could contain sufficient discriminatory information enabling a reliable classification of surface finish quality. This approach not only facilitates in-process monitoring but also provides a foundation for intelligent manufacturing systems capable of real-time quality assurance. Full article

Industries are leveraging the wire laser-beam-directed energy deposition (DED-LB) additive manufacturing (AM) process to manufacture and repair high-quality, defect-free, and cost-effective parts. However, expensive, non-easily accessible, and complex metrology equipment is needed to quantify part-related performance metrics such as cross-sectional dimensional accuracy and intrinsic defects. This information is necessary for establishing the operating process window and for the quality characterization of the part. Therefore, this work presents a methodology that combines information captured from a vision-based monitoring system with the output of Computed Tomography (CT) towards the knowledge generation and process optimization of wire DED-LB. The design of experiments as well as the interpretation of the results are achieved by employing Nested ANOVA where the dependency of cross-sectional stability on the laser power parameter is demonstrated, enabling, at the same time, the understanding of unstructured datasets where multiple parameters vary at different levels. Finally, this work can be the pillar for adopting new production and part requirements while also giving directions about the effect of control strategies on the part quality. Full article