Search Results (350)

The main aim of this study is to investigate the microstructure and microhardness of Wire Arc Additive Manufactured (WAAM) samples produced under different layer deposition strategies and corresponding interlayer temperature conditions. Experimental samples were produced using the WAAM process with X45CrSi9-3 steel. During the experiments, both the number of layers and the thermal conditions (heating and cooling) were systematically varied. This was achieved by fabricating samples consisting of five layers with three beads per layer. The layer deposition procedure was implemented in two different ways: (i) with a waiting period after each layer to allow cooling to room temperature, and (ii) without such a waiting period. Thermal cycles at selected locations within the samples were calculated using simulation modeling. By combining these thermal cycles with the continuous cooling transformation (CCT) diagram, the expected microstructures in the vicinity of these locations were determined. These predictions were supplemented by microstructural analysis and hardness measurements. Particular emphasis was placed on the influence of interlayer temperature and repeated heating and cooling cycles. The analyses enabled the identification of process parameters that facilitate control over microstructure, microhardness, and property gradients. It can be concluded that the interlayer holding time provides an effective means of controlling the microstructure of the workpiece, ranging from predominantly austenitic to predominantly martensitic. Depending on the thermal cycles, the measured microhardness varied within the range of 360–900 HV. Metallographic examination revealed a wide spectrum of non-equilibrium microstructures, including martensite with varying degrees of tempering, retained austenite, pearlite, and bainite. The application of a thermal model to the conducted experiments, combined with the CCT diagram, indicated that the expected microstructures consist predominantly of martensite with varying degrees of tempering, retained austenite, carbides, and, in some cases, up to 5% pearlite. Full article

Wire Arc Additive Manufacturing (WAAM) is a cost-effective and scalable technique for producing large metallic components; however, coarse columnar microstructures, strong crystallographic texture, and significant residual stresses limit its widespread adoption. Hybrid WAAM processes that integrate deformation-based techniques have been developed to address these limitations. This review provides an analysis of deformation-assisted WAAM, covering interlayer rolling, friction stir processing (FSP), machine hammer peening, laser shock peening, and ultrasonic-vibration-assisted techniques. These hybrid techniques introduce additional thermomechanical parameters (strain, strain rate, and applied stress) that significantly influence microstructure evolution. The governing physical metallurgy mechanisms are discussed in detail, including dislocation accumulation, recovery, static and dynamic recrystallization, and severe plastic deformation. Studies from 2022 to 2025 are critically reviewed, highlighting the effectiveness of hybrid WAAM in promoting columnar-to-equiaxed grain transformation, reducing anisotropy, mitigating defects, and improving mechanical properties across aluminum, titanium, steels, and nickel-based alloys. The integration of auxiliary processes such as in situ machining and heat treatment is also discussed. This review establishes a process–structure–property framework for hybrid WAAM and provides guidance for the development of advanced additive manufacturing systems for the production of near-net-shape components, with reported yield-strength gains of 20–40%, elongation gains of 10–30%, and fatigue-life improvements of up to 60% relative to as-built WAAM. Full article

Indisputably, the evolution of innovative manufacturing methods such as additive manufacturing (AM) or 3D printing in the last decade has started gradually to influence the construction field, offering significant benefit potential, particularly in the field of metallic materials. In the case of aluminium alloys, the implementation of the wire arc additive manufacturing (WAAM) method, an AM sub-type, has recently emerged as a promising alternative to conventional rolling and extrusion, enabling unprecedented geometric flexibility, lower energy demand, and reduced tooling costs. However, the selection of an appropriate feedstock alloy poses a major challenge, as inherent trade-offs between strength, ductility, and printing-induced anisotropy arise. In this context, this study presents a thorough multi-scale numerical investigation, spanning from the cross-sectional to the global structural scale. The structural performance of several two-story moment-resisting frames was evaluated, comparing frames featuring WAAM-fabricated columns against conventional extruded and rolled benchmarks. The assessment included three 3D-printed alloys (Al-Mg, Al-Cu, Al-Mg-Si), differing in ductility levels, featuring topology-optimized and internal lattice-reinforced cross-sectional geometries. Linear elastic analyses reveal that global lateral stiffness heavily governs the response of slender frames, where WAAM was able to efficiently decrease the corresponding inter-story drifts by maximizing cross-sectional inertia without necessitating the utilization of larger external member dimensions. Furthermore, nonlinear static (pushover) analyses provided valuable insight into critical design considerations, exposing a profound strength-ductility trade-off in printed aluminium alloy load-bearing members. Full article

Wire arc additive manufacturing (WAAM) demands aluminum feedstock with tightly controlled diameter and high surface integrity. Adding hard TiC nanoparticles is a viable route to enhance the mechanical response of Al wires, yet the associated increase in contact severity can accelerate the wear of wire processing tools, particularly cemented carbide dies. This study elucidates the unidirectional sliding interaction between a TiC reinforced Al WAAM wire, and a WC/Co die material containing 5 wt% Co, using a modified scratch testing configuration under dry and lubricated conditions. Two dominant mechanisms are identified: (i) aluminum adhesion on the die surface and (ii) third body abrasion arising from WC particle pull out, promoted by preferential degradation of the cobalt binder. The presence of TiC nanoparticles reduces both the extent of Al transfer and the intensity of third body abrasion, an effect that is further amplified by lubrication. Consistently, lubrication also diminishes surface defects on the wire after sliding. The results provide a mechanistic basis to balance wire strengthening with tool life and highlight practical levers—nanoparticle reinforcement and lubrication strategies—for mitigating die damage while preserving WAAM wire surface quality. Full article

Wire arc additive manufacturing (WAAM) is an efficient, low-cost technique for fabricating large-scale metallic components and, in particular, functionally graded materials (FGMs). This review focuses on the fabrication of 316L stainless steel–Inconel 625 FGMs by arc-based WAAM processes, examining Gas Metal Arc Welding (GMAW), Gas Tungsten Arc Welding (GTAW) and Plasma Arc Welding (PAW) in terms of their microstructural outcomes, compositional control strategies, residual stress development and mechanical performance. A critical finding emerging from the reviewed literature is that direct compositional interfaces between 316L and Inconel 625 can yield superior tensile strength and ductility and lower residual stresses compared to smooth gradient strategies, owing to the formation of detrimental secondary phases such as δ-phase, Laves phase and MC carbides at intermediate iron–nickel compositions encountered only during graded builds. The potential of Submerged Arc Additive Manufacturing (SAAM) as a future high-deposition-rate alternative for large-scale FGM fabrication is also discussed. Key challenges, including dilution control, Laves phase formation, residual stress management and the corrosion characterization of the graded region, are identified, together with priority research directions for advancing the industrial adoption of arc-based FGM components. Full article

Wire Arc Additive Manufacturing (WAAM) has emerged as a promising additive manufacturing technique due to its high deposition rate and low material cost. WAAM is increasingly adopted in various industries for the production of large-scale metal components, yet optimizing productivity without sacrificing mechanical integrity remains a critical challenge, particularly for low-carbon steels. This study systematically investigates the influence of key WAAM parameters—welding current (100–350 A) and travel speed (5–30 mm/s) on the deposition stability, microstructure, and mechanical properties of thin walls made of low-carbon Fe–0.09 C–1.10 Cr–1.47 Mn–0.59 Si–0.56 Mo–0.11 Ni–0.23 V steel. A stable processing window for defect-free wall fabrication was established for currents of 100–250 A, while higher currents of 300–350 A resulted in melt pool instability and geometrical distortions due to excessive heat input. Microstructural characterization revealed a dual-phase structure consisting of allotriomorphic ferrite (ALF) and acicular ferrite (AF) in all samples. The microstructural evolution was critically governed by variations in the cooling time in the critical temperature range of 800 °C to 500 °C (t_8/5) within the thermal cycles, a direct consequence of the heat input quantified through volumetric energy density. Low heat input at 100 A, 5 mm/s promoted a microstructure with minimal ALF fraction of ~10%, whereas high heat input at 350 A, 30 mm/s induced significant ferrite recrystallization and coarsening, increasing ALF fraction to ~55%. These microstructural changes directly affected mechanical properties: YS/UTS decreased from 512 MPa/668 MPa to 401 MPa/602 MPa, respectively. Concurrently, the deposition rate increased substantially from ~1.6 kg/h to ~6.3 kg/h. The results demonstrate a critical trade-off between productivity and mechanical performance, providing a practical framework for parameter selection in WAAM-fabricated low-carbon steel components. Full article

This study quantitatively evaluates the impact of Wire Arc Additive Manufacturing (WAAM) process parameters on the environmental performance of components produced in Invar 36 alloy. An experimental campaign involving 49 parameter sets was carried out by varying wire feed speed, welding voltage, and welding speed. For each condition, electrical signals, shielding gas consumption, and wire usage were measured and converted into parameter-resolved Life Cycle Inventory (LCI) data. A cradle-to-gate Life Cycle Assessment (LCA) was implemented in SimaPro 9.6 using the European CML-IA baseline v3.10 midpoint method, adopting 1 kg of as-built deposited Invar 36 as the functional unit. Results show that feedstock production represents the dominant hotspot (8.68 kg CO₂-eq/kg), while the WAAM stage contributes between 1.13 and 4.12 kg CO₂-eq/kg, leading to a total impact ranging from 9.81 to 12.80 kg CO₂-eq/kg. As a result, this study demonstrates that process parameter selection strongly influences environmental performance. Indeed, Specific Energy Consumption (SEC) ranges from 0.44 to 1.95 kWh/kg, while argon consumption varies between 0.26 and 1.51 kg/kg of deposited material. By analysing the results and excluding unstable or manufacturing-infeasible deposition regimes, the optimal trade-off between process stability and environmental impact is achieved at approximately WFS = 7 m/min, V = 20 V, and WS = 6.5 mm/s. Beyond quantifying the environmental hotspots of Invar 36 WAAM, this study provides a dedicated, parameter-resolved cradle-to-gate LCA based on experimentally measured foreground data collected across 49 process parameter combinations. By combining environmental assessment with feasibility screening of the investigated deposition regimes, the work identifies not only environmentally favourable conditions, but also parameter regions that are technologically viable for WAAM processing of Invar 36. The resulting dataset provides a benchmark foundation for future sustainability-oriented process optimisation and decision support in WAAM. Full article

Wire Arc Additive Manufacturing (WAAM) has gained attention as a metal additive manufacturing process producing complex large-scale components with high deposition rates and lower costs. Cold Metal Transfer (CMT) offers reduced heat input and enhanced control of metal transfer, making it suitable for aluminium. This review analyses CMT-based WAAM with a focus on Al–Si alloys, providing a synthesis for this material system and establishing a structured comparison of representative studies on process fundamentals, arc mode variants, and key processing parameters. The influence of electrical and kinematic parameters and thermal management on process and geometrical stability, microstructural evolution, defect formation, and mechanical behaviour is discussed. Process behaviour is governed by the temporal distribution of heat input within the CMT cycle and thermal history. Control of heat input can reduce porosity, microstructural heterogeneity, and geometric instability, while advanced CMT modes can improve process stability and material efficiency under appropriate process configurations. Mechanical performance depends on the interaction between process parameters, microstructure, and defects, leading to variability and anisotropy. Despite progress, challenges related to process repeatability, narrow processing windows, defect susceptibility, and predictive capability remain. Future research should focus on parameter optimization, integrated modelling, real-time control, and WAAM-specific alloys to enable reliable industrial implementation. Full article

Wire and arc additive manufacturing (WAAM) offers high deposition efficiency for large-scale aluminum components; however, layer-by-layer thermal cycling often induces microstructural anisotropy and spatial heterogeneity, which compromise structural reliability. In this study, an ultrasonic-based quantitative framework is proposed to evaluate and optimize anisotropy and heterogeneity in WAAM 2319 aluminum alloy. Nine blocks were fabricated using an orthogonal design with three key process parameters: torch travel speed, arc current, and shielding gas flow rate. Ultrasonic velocity and attenuation were employed to construct anisotropy and heterogeneity indicators. Results show that velocity-based anisotropy remains below 0.53%, indicating nearly isotropic elastic stiffness, whereas attenuation-based anisotropy reaches up to 76%, revealing pronounced direction-dependent microstructural and porosity features. Metallographic analysis confirms that grain morphology variation and interlayer porosity jointly govern attenuation responses. Response surface surrogate models were established to correlate ultrasonic indicators with process parameters, and both single- and multi-objective optimizations were performed within the feasible process window. The proposed framework provides a non-destructive, volumetric approach for microstructure-informed process parameter optimization in WAAM aluminum alloys. Full article

In modern production, Wire Arc Additive Manufacturing (WAAM) is becoming an essential technology for manufacturing complex components. However, the complexity of planning such processes constrains their widespread use in production cycles. Using various numerical simulation approaches allows for the investigation of resulting geometries with respect to process parameters, reducing the need for experiment-based process planning. Similar to various subtractive processes, there is increased interest in integrating simulation approaches into digital twin applications for planning and optimization of WAAM processes. This requires dynamic geometry mapping and simulation time comparable to the process duration. In this paper, a numerical simulation employing a Dexel-based geometry representation and a model for single-bead geometry parameter prediction is investigated as a vital alternative to Finite Element Method (FEM)-based simulations. The focus lies on the accuracy of the simulated components with respect to the simulation settings, the time needed for it to complete, and the degree of compliance between the simulated and produced multi-layer structures. Using optimized simulation settings achieves an accuracy loss of under 7% due to geometry discretization, with a simulation time that is approximately 37% faster than the process duration. The simulated components closely correspond to the experimental ones in terms of width and height, with a volumetric similarity ranging from 63.3% to 88.8%. Full article

This paper proposes a dual-modal monitoring system combining visible and infrared imaging to enhance overlap defect detection in wire arc additive manufacturing (WAAM) based on cold metal transfer (CMT) welding for multi-pass builds. Traditional single-modal approaches, primarily relying on melt pool imagery, are often hindered by arc light and spatter interference, which can compromise detection accuracy. In this work, overlap defect refers to insufficient overlap between adjacent tracks, and the dataset is created by inducing overlap defects through inter-track spacing in multi-pass deposition. The proposed dual-modal strategy mitigates these challenges and significantly improves detection precision. A dual-input convolutional neural network model named Multimodal Mutual Fusion Network (MMFNet) was designed, fusing visible and infrared data at the feature level to achieve a prediction accuracy of 98.34%. Comparative experiments with single-modal models demonstrate the superiority of the proposed approach, with single-modal accuracies of only 95.76% (infrared) and 92.85% (visible light). The proposed system provides a robust solution for monitoring of overlap defects in WAAM in the studied multi-pass setting, highlighting the potential of dual-modal systems for improving quality control in additive manufacturing processes. Full article

The main aim of this study was to evaluate the applicability of a low-cost, double-wall gas metal arc welding (GMAW)-based wire arc additive manufacturing (WAAM) process for aluminum alloy AlMg5, with an emphasis on microstructural heterogeneity, layer-dependent defect formation, and their implications for mechanical performance and geometric characteristics. A Taguchi L9 (3³) design of experiments was employed to investigate the influence of welding current (40–60 A), shielding gas flow (10–20 L/min), and arc correction (0–40%) on wall geometry, material utilization, and overall process quality through multi-response optimization. The optimal parameter set (60 A, 15 L/min, 0% arc correction) resulted in a 54.9% improvement in the Grey Relational Grade compared to the lowest-performing configuration. Metallographic analysis revealed heterogeneous grain evolution governed by the multilayer thermal history, with porosity levels ranging from 3.20% to 3.49% and lack-of-fusion defects preferentially concentrated in interlayer and mid-height regions. The fabricated high-wall structure exhibited hardness values between 72 and 85 HV and an average ultimate tensile strength of 175 MPa. The observed mechanical scatter was consistent with localized microstructural heterogeneity and spatial defect distribution. The results demonstrate that geometric evaluation alone is insufficient as a quality metric for WAAM components and must be complemented by metallographic integrity assessment. Overall, the study highlights the importance of direct parameter optimization in double-wall WAAM structures to mitigate defect formation and enhance mechanical reliability under industrially accessible deposition conditions. Full article

The limited ductility of the VW63K rare-earth magnesium alloy fabricated via cold metal transfer wire arc additive manufacturing (CMT-WAAM) was targeted in this work. An integrated approach that combines first-principles calculations with experimental characterization was employed to achieve this goal. This approach was used to systematically investigate how Ag doping alters the microstructure and mechanical properties of the alloy. First-principles calculations performed on the primary precipitate phase Mg₂₄(Gd,Y)₅ demonstrated that Ag atoms preferentially occupy the Mg lattice sites and form pronounced orbital hybridization with neighboring rare-earth atoms. These interactions were found to enhance critical mechanical parameters, including the Cauchy pressure, B/G ratio, and Poisson’s ratio, which are indicative of enhanced ductility and toughness of the phase. Experimental results indicate that the fracture strain of the VW63K-Ag alloy was increased from approximately 4% to above 12% following Ag doping. This resulted in a significant improvement in ductility. The ultimate tensile strength (UTS) underwent only a moderate reduction. Using a closed-loop approach integrating theoretical prediction and experimental validation, the microstructural modification and strengthening mechanisms of Ag in the VW63K alloy fabricated via CMT-WAAM were clarified. These findings offer a theoretical foundation and experimental evidence for compositional design and optimizing additive manufacturing (AM) processes for rare-earth magnesium alloys. Full article

Conventional subtractive manufacturing methods, such as cutting, often result in material waste and limitations in geometric complexity. To address these challenges, Wire Arc Additive Manufacturing (WAAM), in which components are built through successive weld bead deposition, has attracted increasing attention across various industrial fields. However, WAAM-fabricated components typically exhibit significant surface irregularities, necessitating additional post-processing that reduces overall productivity. Improving productivity therefore requires effective control and optimization of deposition parameters. This task is particularly challenging in multilayer WAAM processes, as the geometry of previously deposited layers varies with operating conditions. To address this challenge, this study proposes an AI-based framework for controlling surface roughness by rapidly identifying near-optimal process parameters in response to evolving bead geometry. A large-scale simulation dataset was generated by applying a pre-trained deep neural network (DNN) surface roughness predictor to one million bead geometry variations under 72 process parameter combinations. The resulting optimal parameter labels were used to train a classification model that recommends process conditions based on the current bead geometry. Model performance was evaluated using predictor-estimated surface roughness values, achieving Weighted Precision, Recall, and F1-score of 0.98, with an average AUC of 0.977. Five previously generated WAAM specimens were used for comparative analysis between AI-recommended and conventional process conditions using the previously developed and validated surface roughness prediction model, rather than direct physical measurements. This predictor-based feasibility analysis showed that AI-recommended conditions consistently reduced the predicted surface roughness, indicating the potential of AI-driven process optimization to improve surface quality in WAAM and reduce reliance on post-processing. Full article

This study reviews the application of wire arc additive manufacturing (WAAM) technology in maritime engineering and investigates an experimentally driven analytical approach for prediction of thermal distributions based on the Rosenthal solution. Two ER70S-6 low-carbon steel WAAM cylinders were fabricated using gas metal arc welding (GMAW) and plasma arc welding (PAW) processes, with interlayer temperatures of 453 °C and 250 °C, respectively. Accurately measuring the temperature field to tailor the microstructure has long been a challenge. The results indicated a significant deviation between the analytical predictions and the experimental data. To address this discrepancy, a hybrid approach combining analytical and experimental results was implemented. Time intervals between layers, extracted from the experimental data, were incorporated into the Rosenthal equation to improve the accuracy of temperature field predictions. The microstructure at the bottom, middle, and top regions of the WAAM components was examined using optical microscopy. Tensile testing and Vickers microhardness measurements were conducted to evaluate mechanical properties. Scanning electron microscopy (SEM) was used to analyze fracture surfaces and identify fracture modes. The results were consistent with those reported for other ER70S-6 cylindrical WAAM components. This work highlights limitations of the Rosenthal solution and emphasizes the need for thermal models in WAAM applications. Full article