Search Results (429)

This study investigates the microstructure evolution and mechanical properties of DSS2209 duplex stainless steel fabricated via cold metal transfer wire arc additive manufacturing (CMT-WAAM). The as-deposited thin-wall components exhibit significant microstructural heterogeneity along the build height due to thermal history variations. Optical microscopy, SEM-EDS, and EBSD analyses reveal distinct phase distributions: the bottom region features elongated blocky austenite with Widmanstätten austenite (WA) due to rapid substrate-induced cooling; the middle region shows equiaxed blocky austenite with reduced grain boundary austenite (GBA) and WA, attributed to interlayer thermal cycling promoting recrystallization and grain refinement (average austenite grain size: 4.16 μm); and the top region displays coarse blocky austenite from slower cooling. Secondary austenite (γ₂) forms in interlayer remelted zones with Cr depletion, impacting pitting resistance. Mechanical testing demonstrates anisotropy; horizontal specimens exhibit higher strength (UTS: 610 MPa, YS: 408 MPa) due to layer-uniform microstructures, while vertical specimens show greater ductility (elongation) facilitated by columnar grains aligned with the build direction. Hardness ranges uniformly between 225–239 HV. The study correlates process-induced thermal gradients (e.g., cooling rates, interlayer cycling) with microstructural features (recrystallization fraction, grain size, phase morphology) and performance, providing insights for optimizing WAAM of large-scale duplex stainless steel components like marine propellers. Full article

This review explores the evolution and current state of machine learning (ML) and artificial intelligence (AI) applications in direct energy deposition (DED) and wire arc additive manufacturing (WAAM) processes. A Python-based automated search script was developed to systematically retrieve relevant literature using the Crossref API, yielding around 370 papers published between 2010 and July 2025. The study identifies significant growth in ML-related DED research starting in 2020, with increasing adoption of advanced techniques such as deep learning, fuzzy logic, and hybrid physics-informed models. A year-by-year trend analysis is presented, and a comprehensive categorization of the literature is provided to highlight dominant application areas, including process optimization, real-time monitoring, defect detection, and melt pool prediction. Key challenges, such as limited closed-loop control, lack of generalization across systems, and insufficient modeling of deposition-location effects, are discussed. Finally, future research directions are outlined, emphasizing the need for integrated thermo-mechanical models, uncertainty quantification, and adaptive control strategies. This review serves as a resource for researchers aiming to advance intelligent control and predictive modeling in DED-based additive manufacturing. Full article

In this study, high-temperature uniaxial tensile tests were performed on IN718 superalloy samples fabricated using Wire Arc Additive Manufacturing (WAAM) and compared to wrought IN718 superalloy samples. The mechanical properties and Portevin–Le Chatelier (PLC) behavior of WAAM IN718 were analyzed, with particular attention paid to its anisotropy and differences from its wrought counterpart. WAAM specimens were obtained from three distinct orientations within the printed blocks. The results indicated that WAAM IN718 exhibited a higher yield strength but reduced failure elongation compared to wrought IN718. Among the WAAM samples, the yield strength was highest in the transverse direction, followed by the in-depth direction, and lowest in the growth direction. Post-aging treatment significantly increased the yield strength of WAAM IN718. WAAM IN718 showed a larger critical strain for the onset of serrated flow and smaller stress drop amplitudes compared to wrought IN718 under the PLC effect. Furthermore, as the strain rate decreased, PLC serrations in WAAM specimens from the in-depth direction transitioned from type A to type C. Conversely, specimens from the growth direction maintained type B serrations at a strain rate of ${10}^{-4}{\mathrm{s}}^{-1}$. This study also examined potential factors influencing the differences in PLC behavior and conducted an analysis of the fracture surfaces across various specimens. Full article

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing (WAAM) advanced as a promising additive manufacturing process to realize the fabrication of these structures due to its high deposition rate, cost-effectiveness, and material utilization efficiency. This review presents a comprehensive overview of the recent progress, processing strategies, and scientific challenges in WAAM of multi-material structures. The paper begins with an introduction to multi-material structures, followed by a bibliometric analysis of the current research landscape. Conventional and additive manufacturing fabrication approaches are presented. The review highlights key developments in processing strategies and critically evaluates research studies on WAAM of BS and FGMs. Major scientific challenges, including porosity, lack of fusion, residual stresses, cracking, material compatibility, and brittle intermetallic phase formation, are critically analyzed. Additionally, modeling, simulation, and process automation issues are discussed as barriers to industrial-scale implementation. The paper concludes with an outlook on future research directions to address existing challenges and accelerate the adoption of WAAM for complex multi-material components. Full article

The objective of this study was to characterize austenitic stainless steel 310 produced by Wire and Arc Additive Manufacturing (WAAM), addressing a gap in the literature regarding this alloy. Microstructural, chemical, and mechanical analyses were performed. Optical and electron microscopy revealed a predominantly columnar grain structure with characteristic tracks along the deposition direction. Point and mapping EDS analyses indicated a homogeneous distribution of iron, chromium, and nickel; however, point measurements suggested a possible underestimation of nickel, likely due to high relative error. Tensile tests demonstrated anisotropic mechanical behavior, with yield strength meeting standards at 45° and 90°, but lower at 0°. Ultimate tensile strength and elongation were below conventional requirements, with a maximum elongation of 15% at 90°. Additionally, the sample exhibited a total porosity of approximately 0.89%, which contributes to the reduction in mechanical properties, especially in the direction parallel to the deposition tracks. Overall, the WAAM-produced 310 stainless steel presented a microstructure similar to hot-rolled and annealed AISI 310 steel, but with distinctive features related to the additive process, such as mechanical anisotropy and microstructural directionality. These limitations highlight the need for process optimization to improve mechanical performance but reinforce the alloy’s structural potential in additive manufacturing. Full article

Wire Arc Additive Manufacturing holds promise for on-board metal part production in maritime settings, yet its implementation remains limited due to the vibrational instability inherent to shipborne environments. This study addresses this critical technological barrier by analyzing the effects of marine vibrations on process stability and proposing an integrated solution based on adaptive process control, gyrostabilized platforms, and real-time monitoring systems. The research establishes specific technical requirements for WAAM instrumentation under maritime conditions and evaluates the capabilities and limitations of existing hardware and software tools. A set of engineering recommendations is presented for improving digital modeling, thermal–mechanical monitoring, and feedback control systems. Additionally, the study highlights material-related challenges by examining the influence of alloy properties on print quality under dynamic loads. The proposed approach enhances WAAM process resilience, laying the groundwork for reliable, high-quality additive manufacturing at sea. These findings are particularly relevant to shipboard maintenance, repair, and remote fabrication tasks, marking a significant step toward the industrial adoption of WAAM in marine engineering. Full article

Additive manufacturing (AM) is an Industry 4.0 technology that assists or replaces the conventional manufacturing (CM) of complex geometries in various sectors, including transport, steel, aerospace, military, and architecture. The aim is to improve processes, reduce energy consumption, atmospheric emissions, and solid waste, and streamline stages while complying with the new environmental regulations. The main objective of this work was to carry out a cradle-to-gate Life Cycle Assessment (LCA), considering the raw material extraction, pre-processing, manufacturing, and post-processing stages, comparing two manufacturing methods for the same ER-90 metal flange part, conventional forging and wire and arc additive manufacturing (WAAM), all following the requirements and operations proposed by the ISO 14040/44 standard. WAAM is a Directed Energy Deposition (DED) technology that uses welding techniques to produce 3D objects with more complex geometries. Compared to the forging industry, which requires a lot of heat and kinetic energy in its metal part production stages, WAAM is a more sustainable and modern alternative because it does not require high temperatures and energy to produce the same parts. The environmental indicators compared in the process stages were energy consumption, greenhouse gas (GHG) emissions, and solid waste. The total energy consumption in AM was 18,846.61 MJ, the GHG emissions were 864.49 kgCO₂-eq, and the solid waste generated was 142.34 kg, which were 63.8 %, 90.5%, and 31.6% lower than the environmental indicators calculated for CM, respectively. Full article

DC arcs are widely used in many fields such as shipbuilding, machinery manufacturing, and aerospace due to their advantages of high energy density, simple structure, and low price. However, there are few studies on the sensitivity of the arc pressure and temperature fields to current and protective gas flow rate. In order to solve this problem, this paper establishes a numerical model for the coupling of DC arc electric–thermal–flow multi-physical fields. Based on this model, the variation rules of the arc temperature, pressure, and potential field with current or protective gas flow rate are studied, respectively, when the current is 100–600 A or the gas flow rate is 18–48 L/min. The results show that the current is the most important factor in the sensitivity of the arc temperature and potential field to the current and protective gas flow rate. With the increase in current, the Joule heat power increases significantly, and the arc central temperature shows a nonlinear increase to 27,000 K. With increasing current, the peak of the pressure field gradually shifts to the region below the top of the wire arc, and the highest pressure increases by 14 times. When the current is small, the increase in argon flow rate can inhibit the spreading of the temperature field by forced convection; when the current is large, the arc contraction with an increasing argon flow rate leads to an anomalous increase in the arc-central temperature. In addition, the energy accumulation mechanism in the strong-current–high-flow-rate coupling region is also revealed, a coupled mathematical model of arc contraction and turbulent loss under the Lorentz force is constructed, and the thermodynamic properties of the arc under the coupling of multi-physical fields are elucidated. Full article

Manufacturing processes are inherently complex, multi-objective in nature, and highly sensitive to process parameter settings. This paper presents two simple and efficient optimization algorithms—Best–Worst–Random (BWR) and Best–Mean–Random (BMR)—developed to solve both constrained and unconstrained optimization problems of manufacturing processes involving single, multi-, and many-objectives. These algorithms are free from metaphorical inspirations and require no algorithm-specific control parameters, which often complicate other metaheuristics. Extensive testing reveals that BWR and BMR consistently deliver competitive, and often superior, performance compared to established methods. Their multi- and many-objective extensions, named MO-BWR and MO-BMR, respectively, have been successfully applied to tackle 2-, 3-, and 9-objective optimization problems in advanced manufacturing processes such as friction stir processing (FSP), ultra-precision turning (UPT), laser powder bed fusion (LPBF), and wire arc additive manufacturing (WAAM). To aid in decision-making, the proposed BHARAT can be integrated with MO-BWR and MO-BMR to identify the most suitable compromise solution from among a set of Pareto-optimal alternatives. The results demonstrate the strong potential of the proposed algorithms as practical tools for intelligent decision-making in real-world manufacturing 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

Process control and quality assurance of wire + arc additive manufacturing (WAAM) and automated welding rely heavily on in-process monitoring videos to quantify variables such as melt pool geometry, location and size of droplet transfer, arc characteristics, etc. To enable feedback control based upon this information, an automatic and robust segmentation method for monitoring of videos and images is required. However, video segmentation in WAAM and welding is challenging due to constantly fluctuating arc brightness, which varies with deposition and welding configurations. Additionally, conventional computer vision algorithms based on greyscale value and gradient lack flexibility and robustness in this scenario. Deep learning offers a promising approach to WAAM video segmentation; however, the prohibitive time and cost associated with creating a well-labelled, suitably sized dataset have hindered its widespread adoption. The emergence of large computer vision models, however, has provided new solutions. In this study a semi-automatic annotation tool for WAAM videos was developed based upon the computer vision foundation model SAM and the video object tracking model XMem. The tool can enable annotation of the video frames hundreds of times faster than traditional manual annotation methods, thus making it possible to achieve rapid quantitative analysis of WAAM and welding videos with minimal user intervention. To demonstrate the effectiveness of the tool, three cases are demonstrated: online wire position closed-loop control, droplet transfer behaviour analysis, and assembling a dataset for dedicated deep learning segmentation models. This work provides a broader perspective on how to exploit large models in WAAM and weld deposits. Full article

In recent years, with the innovation and continuous development of additive manufacturing technology, research on wire arc additive manufacturing technology (WAAM) has become increasingly common and in-depth in the chemical industry, mold manufacturing, and other fields. Therefore, it has attracted the attention of many universities, research institutes, and aerospace industries, conducted in-depth research on WAAM technology, and achieved certain research results. This paper briefly summarizes the current research status of arc additive manufacturing technology and summarizes the application status of WAAM technology in product development, personalized customization, traditional process replacement, “material–structure–function” integration, mold repair, etc. WAAM technology has huge development potential and good application prospects. In the future, arc additive manufacturing will develop in the direction of intelligence and high precision. Full article

Wire and arc additive manufacturing (WAAM) is a promising method of producing medium- and large-sized aluminum alloy structures, though it faces challenges such as porosity, residual stresses and inconsistent mechanical properties. This study investigates the effect of current type (AC and DC MIG welding) and polarity balance (influencing the duration of the positive/negative period of the cycle) on the mechanical and microstructural properties of 6063 aluminum alloy walls produced by WAAM. A TiB₂-refined Al–Mg–Si (6063) filler wire, specifically developed for arc-based processing, was used. Tensile tests, Vickers hardness measurements (HV5), optical microscopy and X-ray diffraction based on cosα method were used to evaluate performance in terms of strength, ductility, hardness, grain structure, porosity and residual stress. The results showed that the balance of AC polarity significantly affects wall geometry, porosity and grain structure. Increasing the negative polarity period resulted in taller and narrower walls, while the widest walls were produced with increased positive polarity. Residual stress measurements revealed a tensile–compressive–tensile distribution, with the DC-MIG samples showing the highest surface stress values. The highest tensile strength (172 MPa) was measured in the lower region of the DC-MIG sample, suggesting that areas near the substrate benefit from faster cooling. Full article

Wire Arc Additive Manufacturing (WAAM), a specific type of Directed Energy Deposition (DED) additive manufacturing, has recently gained widespread attention for manufacturing industrial components. WAAM has many advantages compared to other metal AM processes such as powder bed fusion. It is not only cost-efficient and easily accessible, but also capable of manufacturing large-scale industrial components in a short period of time. However, due to the inherent layered nature of the process and significant heat accumulation, parts can experience severe warping, often leading to part rejection. Predicting these anomalies prior to manufacturing would allow for process parameter adjustments to reduce or eliminate residual stresses and large deformations. In this study, we develop a simulation-based model capable of accurately predicting final deformations and unintended warpages. A Johnson–Cook plasticity model with isotropic hardening is implemented through a UMAT user subroutine in Abaqus. The proposed model is then utilized to predict the residual stresses and deformations in WAAM-fabricated parts. Simple wall geometries with 4, 8, and 20 layers deposited on build plates of varying thicknesses, are tested to assess the performance of the model. Combined Johnson–Cook plasticity and isotropic hardening for the WAAM process were implemented for the first time in this study, and the model was validated against experimental data, showing a maximum deviation of 4%. Thermal analysis of a four-layer-high wall took 12 min, while structural analysis using the proposed model took 1 h and 40 min. In comparison, thermo-mechanical analysis of the same geometry reported in the literature takes 14 h. The results demonstrate that the proposed model is not only highly accurate in predicting warpage but also significantly faster than other methodologies reported in the literature. Full article

Additive manufacturing (AM) stands out for its variable applications in terms of material, quality, and geometry. Wire Arc Additive Manufacturing (WAAM) is remarkable for producing large parts in reduced times when compared to other AM methods. The possibility of producing a part with a near-net shape not only enhances productivity but also reduces resources usage. However, parts produced by WAAM may need post-processing by machining to achieve functional surface requirements. Therefore, it is important that machining, even if minimized, does not lead to a significant environmental impact. In this sense, this work evaluates the effect of using compressed air, dry cut, and synthetic biodegradable cutting fluid at varying nozzle positions and flow rates on the surface quality of ER70S-6 steel produced by WAAM, after milling with TiAlN-coated carbide tools. To analyze the surface roughness, parameters Ra, Rq, and Rz were measured and microscopy was used to further evaluate the surfaces. The surface hardness was also evaluated. The results showed that a flow rate of 10 L/min promotes better surface quality, which can be further improved using compressed air, leading to a surface quality 50% better when compared to dry cutting. Dry cut was not suitable for machining ER70S-6 WAAM material as it resulted in rough surface texture with an Rz = 4.02 µm. Compressed air was the best overall condition evaluated, achieving a 36% Ra reduction compared to dry cutting, the second-lowest hardness deviation at 6.51%, and improved sustainability by eliminating the need for cutting fluid. Full article