Search Results (68)

Ti-6Al-4V has seen widespread adoption in the aerospace industry due to its advantageous material properties, but the alloy is costly to produce with vulnerable supply chains. Repair and remanufacture offer economic and environmental benefits over scrapping components. Powder-based additive-manufacturing processes have been investigated; however, coaxial wire laser metal deposition (LMD) remains understudied in repair scenarios, and the transfer of planar process parameters to inclined geometries for complex repairs has not been established. This paper identifies a process window for 1.2 mm Ti-6Al-4V wire and applies the parameters to repair a trapezoidal groove. Tensile and fatigue properties are evaluated, and fractography is conducted using optical and scanning electron microscopy. Findings show the transfer from planar to inclined geometry induces evolving geometric and thermal boundary conditions, including underbuilding and thermal accumulation. Nonetheless, the repair exhibited a yield strength of 868.2 MPa, an ultimate tensile strength of 920.5 MPa, and an elongation of 8.9%. Moreover, UFT revealed a fatigue performance of the repairs that was consistent with heat-treated SLM materials. Fractographic analysis revealed triangular defects and feedstock contamination that contribute to reduced repair properties. As such, this paper demonstrated that coaxial wire-LMD can be used to deposit material into complex geometries, but a complete, defect free repair was not achieved. Full article

Additive manufacturing (AM) enables rapid, near-net-shape fabrication with high material efficiency, but the resulting components often exhibit surface roughness, microstructural heterogeneity, and tensile residual stresses that reduce their performance. Machine hammer peening (MHP) is a mechanical surface treatment capable of modifying the surface integrity of AM components. It can be applied either as a conventional post-processing step after fabrication or as a hybrid interlayer treatment integrated into the build process. In this study, the effects of MHP process parameters and treatment strategies on wire-based laser metal deposition (LMD-w) Inconel 718 components were investigated, including the implementation of hybrid interlayer MHP. Surface topography, hardness, microstructure, and residual stresses were examined experimentally, while numerical simulations were developed to support the measurements and to characterize local contact conditions and plastic strain evolution during peening. The results show that MHP significantly reduces surface waviness and roughness, increases near-surface hardness, refines the microstructure, and introduces deep compressive residual stresses. Furthermore, hybrid interlayer MHP enhances the depth and uniformity of the modified layer by influencing the evolving microstructure during deposition. Standard forged Inconel 718 samples were also treated with MHP as a reference, showing comparable characteristics between the forged and AM components. These findings demonstrate that MHP is a versatile and effective modification technique for improving the performance and reliability of AM components, particularly when implemented as a hybrid interlayer treatment during the AM process. Full article

Additive–subtractive hybrid manufacturing (ASHM) allows for the rapid manufacturing of metal components with complex and precise geometries for ready-to-use or near-ready-to-use applications. Laser wire-directed energy deposition (LW-DED) can be used to quickly manufacture metal components, while CNC machining can achieve precise geometric tolerances. In this study, Ti-6Al-4V alloy specimens were fabricated using an LW-DED process combined with CNC machining and tested to evaluate the effects of ASHM on mechanical performance. Post fabrication, the Ti-6Al-4V material was evaluated through hardness mapping, monotonic tensile testing, and fully reversed axial fatigue testing. Vicker’s micro-hardness mapping showed a range of hardness results from 300 to 350 HV in the ASHM Ti-6Al-4V that remained consistent throughout the build. Tensile results showed a similar response to cast and wrought Ti-6Al-4V, with an average yield stress of 819.4 MPa, ultimate tensile strength of 935.5 MPa, and modulus of 119 GPa. When tested in fatigue, the material had a reduced life compared to wrought Ti-6Al-4V, which is attributed to defects originating from the additive process. While no run-outs were observed from the testing, the fatigue results remain aligned with trends reported for other methods of additively manufactured Ti-6Al-4V. Fully reversed high-cycle fatigue loading revealed that the ASHM-fabricated Ti-6Al-4V fell into a Basquin power-law fit with a fatigue strength coefficient of 1942 MPa with a fatigue strength exponent of −0.115. The fatigue life of the ASHM material is found to be dependent on the resulting porosity of the material that stems from the LW-DED process used in the ASHM process described. Full article

Additive manufacturing (AM), also known as three-dimensional (3D) printing, has emerged as a revolutionary digital near-net-shape manufacturing technology, offering innovative solutions for the design and fabrication of complex, high-performance structures and equipment. This paper reviews the recent advancements and applications of metal AM technologies in the marine sector. Firstly, the principles and characteristics of three most widely adopted metal AM processes in this field are introduced: laser powder bed fusion (L-PBF), directed energy deposition (DED), and wire arc additive manufacturing (WAAM). Subsequently, the application status of metal AM is summarized in four key marine sectors: propulsion systems, underwater vehicle housings and structures, hull structures and shipboard equipment and components, as well as marine equipment repair and emergency support. Building on this, the major challenges for metal AM applications in the marine environment are further discussed, including the fabrication of large-scale components, standardization of materials and processes, integration of smart manufacturing and digital technologies, and sustainability and circular manufacturing. Finally, future trends are projected toward higher efficiency, intelligence, and environmental sustainability. It is indicated that metal AM will fundamentally reshape the manufacturing mode of marine equipment and support its high-performance, low-cost, intelligent and rapid-response development. Full article

Titanium matrix composites (TMCs) are increasingly vital in aerospace for their high specific strength and wear resistance, with compositional gradient design serving as a key strategy to mitigate thermophysical mismatches between ceramic and metal phases. This study utilized laser-directed energy deposition with concurrent wire-powder feeding (LDED-WP) to fabricate TiC/Ti6Al4V gradient composites, employing a laser power of 2700 W, wire feed rates of 110–150 cm/min, and calibrated powder feed rates ranging from 50.22 to 497.13 g/h. Along the build direction, the TiC content was progressively increased from 10 wt.% to 60 wt.%. Investigations into microstructural evolution revealed that the reinforcement morphology transitions from chain-like eutectic TiC to dendritic primary TiC, while the lamellarα-Ti width refines significantly from 4.07 ± 1.15 μm to 0.45 ± 0.29 μm. EBSD analysis confirmed that higher TiC concentrations weaken the characteristic <001> solidification texture, reducing intensity from 11.24 to 7.64. Furthermore, KAM analysis highlighted that thermal expansion and elastic modulus mismatches trigger substantial geometrically necessary dislocation (GND) accumulation at interfaces. Consequently, Vickers hardness improved by 164% along the gradient, peaking at 950 HV. Although the composite achieved an ultimate tensile strength of 630 MPa, the elongation was limited to 2.4% due to crack nucleation in TiC-rich regions and interfacial instability. Full article

Laser-directed energy deposition (DED) using wire or powder feedstock is a promising way to fabricate prototypes in rapid time, including complex metal parts for advanced engineering applications. In this work, AISI 316L stainless steel—a well-known, weldable alloy model—was used to perform a foundational comparative study of wire-fed (LW-DED) and powder-fed (LP-DED) processes, establishing a baseline before progressing to high-temperature alloys. Hollow cylindrical specimens were fabricated and characterized microstructurally and mechanically. LP-DED produced a refined cellular–dendritic structure with primary dendrite arm spacing of 3.29 ± 0.49 µm and slightly higher average hardness (226 ± 8 HV0.2), accompanied by fine, spherical porosity inherent to the powder feedstock. LW-DED generated coarser epitaxial columnar dendrites (5.15 ± 0.69 µm) and slightly lower hardness (206 ± 10 HV0.2) but achieved nearly full density and high material catching efficiency. The results indicate that both methods yield comparable deposits when parameters are controlled, with LP-DED offering enhanced microstructural refinement and LW-DED providing faster deposition and higher build volume. These findings provide practical guidance for the additive manufacturing of high-performance parts and establish a baseline for the application of DED processes to advanced alloys. Full article

Laser wire directed energy deposition (LWDED) has garnered significant attention for the fabrication of large metallic components. However, the complex coupling effects among its process parameters pose challenges for porosity control. Optimizing parameter combinations to effectively minimize porosity is therefore critical to the broader adoption of this technology. In this study, systematic experiments and modeling were conducted to optimize the LWDED process parameters and predict porosity. First, single-factor and orthogonal experiments were performed to evaluate the individual effects of laser power, scanning speed, wire feeding speed, and air pressure on porosity. Subsequently, range analysis and analysis of variance were employed to determine the influence of each parameter and the significance of their interactions. Four machine learning models—SVR, RF, GPR, and XGBoost—were then trained and compared. Among them, the SVR model exhibited the best predictive performance, achieving an R² of 0.8960, an RMSE of 0.19, and an MAE of 0.15, outperforming the other three models. Based on this, the SVR model was further utilized to establish the mapping between process parameters and porosity. Contour maps and three-dimensional surface plots were generated to visualize porosity variation patterns under interacting parameters. Validation experiments showed that the maximum relative error between model predictions and experimental measurements was 0.514%, with an average error of 0.251%. This study provides a reliable reference for selecting low-porosity parameter combinations in the LWDED fabrication of 5356 aluminum alloy components. Full article

The COVID-19 pandemic critically emphasized the need for rapid, flexible, and decentralized manufacturing solutions to support the urgent demand for essential medical equipment, such as oximeters. Metal wire directed energy deposition—w-DED, also known as w-LMD (wire laser metal deposition)—combines the benefits of high material utilization, increased printing speed, and reduced waste, making it an attractive alternative to traditional powder-based processes, especially under time-sensitive and resource-constrained conditions. This work presents a case study focusing on the design and fabrication of injection molds for oximeter casings using metal-wire-based DED. Martensitic stainless steel AISI-420 wire was employed as feedstock and processed via laser wire additive manufacturing to produce a robust, near-net-shape mold suitable for plastic injection molding. The material was selected due to good corrosion and wear resistance. However, poor ductility and toughness, together with AM-induced anisotropy, were the main challenges to address. Therefore, a multi-step methodology was defined to study the effect of different process parameters, which was validated through printing trials, and the optimum process parameter set was identified. The process enabled the rapid construction of intricate mold geometries, minimizing lead times and allowing for quick design iterations. Microstructural and physical properties such as microhardness of the as-built molds were thoroughly characterized. This case study not only illustrates the technical feasibility of producing functional injection molds via metal w-DED but also outlines its role as a resilient manufacturing pathway, capable of meeting emergent healthcare needs and supporting broader industrial applications in a post-pandemic context. Full article

This study investigates the effect of Interlayer Dwell Time (IDT) on the thermal behavior of the Wire-Laser Directed Energy Deposition (WLDED) process. A two-dimensional transient thermal model was developed in MATLAB, incorporating temperature-dependent material properties, a moving Gaussian heat source, and melting–solidification phase change to simulate sequential layer deposition. The model was calibrated for thin-walled geometries, numerically validated using ANSYS, and experimentally validated with literature data. Using the validated model, twenty-seven cases were simulated to examine the combined influence of IDT, part length, and layer thickness on melt-pool dimensions and layer-wise temperature distribution. The results show that increasing IDT reduces melt-pool depth and length by limiting heat accumulation, with the magnitude of this effect depending strongly on part length and layer thickness. Shorter parts and thicker layers exhibit the highest sensitivity to IDT variations. Additionally, the Thermal Stability Factor (TSF) is introduced, a dimensionless index that effectively identifies heat-accumulation phenomena and indicates thermal instabilities. Overall, the findings enhance the understanding of the impact of IDT in the thermal profile of WLDED and demonstrate that optimized IDT selection can stabilize melt-pool geometry and reduce thermal buildup, supporting future adaptive IDT strategies in wire-based metal additive manufacturing. Full article

In the context of Industry 4.0, new methods of manufacturing, monitoring, and data generation related to industrial processes have emerged. Over the last decade, a new method of part manufacturing that has been revolutionizing the industry is Additive Manufacturing, which comes in various forms, including the more traditional Fusion Deposition Modeling (FDM) and the more innovative ones, such as Laser Metal Deposition (LMD) and Wire Arc Additive Manufacturing (WAAM). New technologies related to monitoring these processes are also emerging, such as Cyber-Physical Systems (CPSs) or Digital Twins (DTs), which can be used to enable Artificial Intelligence (AI)-powered analysis of generated big data. However, few works have dealt with a comprehensive data analysis, based on Digital Twin systems, to study quality levels of manufactured parts using 3D models. With this background in mind, this current project uses a Digital Twin-enabled dataflow to constitute a basis for a proposed data analysis pipeline. The pipeline consists of analyzing metal AM-manufactured parts’ surface roughness quality levels by the application of a Deep Neural Network (DNN) analytical model and enabling the assessment and tuning of deposition parameters by comparing AM-built models’ 3D representation, obtained by photogrammetry scanning, with the positional data acquired during the deposition process and stored in a cloud database. Stored and analyzed data may be further used to refine the manufacturing of parts, calibration of sensors and refining of the DT model. Also, this work presents a comprehensive study on experiments carried out using the CW-GTAW (Cold Wire Gas Tungsten Arc Welding) process as the means of depositing metal, resulting in hollow parts whose geometries were evaluated by means of both 3D scanned data, obtained via photogrammetry, and positional/deposition process parameters obtained from the Digital Twin architecture pipeline. Finally, an adapted PointNet DNN model was used to evaluate surface roughness quality levels of point clouds into 3 classes (good, fair, and poor), obtaining an overall accuracy of 75.64% on the evaluation of real deposited metal parts. Full article

The wire Laser-based Directed Energy Deposition (DED-LB) metal additive manufacturing (AM) process is time- and cost-effective, providing high-quality, dense parts while supporting multi-scale manufacturing, repair, and repurposing services. However, its ability to consistently produce parts of uniform quality depends on process stability, which can be achieved through monitoring and controlling key process phenomena, such as heat accumulation and variations in the distance between the deposition head and the working surface (standoff distance). Part quality is closely linked to achieving predictable melt pool dimensions and stable thermal conditions, which in turn influence the end-part’s cross-sectional stability, overall dimensions, and mechanical properties. This work presents a workflow that correlates process and metrology data, enabling the determination of tunable process parameters and their operating process window. The process data are acquired using a vision-based monitoring system and a load-cell embedded in the deposition head, which together detect variations in melt pool area and standoff distance during the process, while metrology devices assess the part quality. Finally, this monitoring setup and its ability to capture the complete process history are fundamental for developing in-line control strategies, enabling optimized, supervision-free, and repeatable processes. Full article

Effective thermal management is essential in metal additive manufacturing to ensure process stability and desirable material properties. Directed energy deposition using a laser beam and wire (DED-LB/w) enables the production of large, high-performance components but remains sensitive to adverse thermal effects during multi-layer deposition due to heat accumulation. While prior studies have investigated interlayer temperature control and substrate preheating in DED modalities, including laser-powder and arc-based systems, the influence of substrate preheating in DED-LB/w has not been thoroughly examined. This study employs substrate preheating to simulate heat accumulation and assess its effects on melt pool geometry, wire–melt pool interaction, and the microstructural evolution of Alloy 718. Experimental results demonstrate that increased substrate temperatures lead to a gradual expansion of the melt pool, with a notable transition occurring beyond 400 °C. Microstructural analysis reveals that elevated preheat temperatures promote coarser secondary dendrite arm spacing and the development of wider columnar grains. Moreover, Nb-rich secondary phases, including the Laves phase, exhibit increased size but relatively unchanged area fractions. Observations from electrical conductance measurements and coaxial visual imaging show that preheat temperature significantly affects the process dynamics and microstructural evolution, providing a basis for advanced process control strategies. Full article

Companies are increasingly turning to additive manufacturing as the demand for one-off 3D-printed metal parts rises. The differences in available additive manufacturing technologies necessitate considering both cost and externalities to select the most suitable alternative. This study compares some of the most prevalent metal additive manufacturing technologies through a shop floor-level operational analysis. A steel robotic gripper is considered as a case study, based on which of the complex, interconnected operational factors that influence costs over time are analyzed. The developed cost model facilitates the estimation of costs, identification of cost drivers, and analysis of the impact of various operations management decisions on overall costs. We found that cost performance across Powder-Bed Fusion (PBF), Wire Arc Additive Manufacturing (WAAM), and CNC machining is determined by part design, quantity, and machine utilization. Although producing parts with complex internal features favors additive manufacturing, CNC outperforms in terms of economy of scale. While PBF offers excellent design freedom and parallel production, it incurs high fixed costs per build in under-utilized situations. A rough but fast method, such as Directed-Energy Deposition (DED)-based additive manufacturing, is believed to be more cost-efficient for large, simple shapes, but is not suitable when fine details are required. Laser-based DED approaches address this limitation of WAAM. Full article

Directed Energy Deposition is an additive manufacturing subgroup that uses a laser beam to melt the wire or powder to create a melt pool. In the current study, a scientometric analysis has been carried out to analyze the contribution of countries, publication type analysis, distribution of publications over the years, keywords analysis, author analysis, cited journal, categories, institutes of publication, and report the practical implications. Firstly, the database was extracted from the Web of Science and then post-processed with CiteSpace 6.2.R4 and VOSviewer 1.6.20 software. Afterward, the associated results had been extracted and reported. It was found that China is the leader according to publication, followed by the USA and Germany, which mostly published their achievements in article and proceeding paper formats, which are increasing annually. According to the keywords, additive manufacturing, Laser Metal Deposition, and fabrication are the most commonly used. Based on the CiteSapce and VOSviewer results, Lin, Xin and Huang, Weidong are the authors with the highest publication rates. In addition, Additive Manufacturing, Materials & Design, and Materials Science and Engineering: A are the most cited journals, and regarding the categories, materials science, multidisciplinary, applied physics, and manufacturing engineering are the most commonly used DED processes. Northwestern Polytechnical University, Fraunhofer Gesellschaft, and the United States Department of Energy (DOE) have performed the most research in the field of DED. Full article

Digital Twins (DTs) are transforming manufacturing by bridging the physical and digital worlds, enabling real-time insights, predictive analytics, and enhanced decision making. In Industry 4.0, DTs facilitate automation and data integration, while Industry 5.0 emphasizes human-centric, resilient, and sustainable production. However, implementing DTs in robotic metal additive manufacturing (AM) remains challenging because of the complexity of the wire-based laser metal deposition (LMD) process, the need for real-time monitoring, and the demand for advanced defect detection to ensure high-quality prints. This work proposes a structured DT architecture for a robotic wire-based LMD cell, following a standard framework. Three DT implementations were developed. First, a real-time 3D simulation in RoboDK, integrated with a 2D Node-RED dashboard, enabled motion validation and live process monitoring via MQTT (message queuing telemetry transport) telemetry, minimizing toolpath errors and collisions. Second, an Industrial IoT-based system using KUKA iiQoT (Industrial Internet of Things Quality of Things) facilitated predictive maintenance by analyzing motor loads, joint temperatures, and energy consumption, allowing early anomaly detection and reducing unplanned downtime. Third, the Meltio dashboard provided real-time insights into the laser temperature, wire tension, and deposition accuracy, ensuring adaptive control based on live telemetry. Additionally, a prescriptive analytics layer leveraging historical data in FireStore was integrated to optimize the process performance, enabling data-driven decision making. Full article