Search Results (286)

Metal additive manufacturing (AM) techniques such Direct Energy Deposition (DED), Powder Bed Fusion (PBF), and Wire Arc Additive Manufacturing (WAAM) enable the production of complex metal components built at rapid rates. Because of the complexity of the process, including high thermal gradients, residual stress, and parameter optimization, these techniques pose significant challenges necessitating the need for advanced computational modeling. A powerful technique to reduce or, in some cases, eliminate these challenges at a much lower cost compared to trial-and-error experiments, is Finite Element Analysis (FEA). This study provides a comprehensive review of the FEA techniques being used and developed to model metal AM processes focusing on the thermal, mechanical, and coupled thermo-mechanical models in DED, PBF, and WAAM. Key topics include heat transfer, residual stress and distortion prediction, microstructure evolution and parameter optimization. Recent advancements in FEA have improved the accuracy of AM process simulations, reducing the need for costly experimental testing, though there is still room for improvement and further development of FEA in metal AM. This review serves as a foundation for future work in the metal AM modeling field, enabling the development of optimized process parameters, defect reduction strategies and improved computational methodologies for high-fidelity simulations. Full article

The simulation of additive manufacturing processes, such as Wire Arc Additive Manufacturing (WAAM), is becoming increasingly important to predict material and component properties in advance of the real-life manufacturing. In contrast to prior work focusing on the simulation of simplified WAAM parts, this paper presents an investigation into the thermo-mechanical finite element (FE) simulation of the manufacturing of large-scale WAAM components. The investigation focuses on various problems within the individual steps of the FE workflow wherein ABAQUS influences the modeling of large-scale components. The investigations are founded upon a thermo-mechanically coupled FE model in ABAQUS 2020. For this purpose, several thermo-mechanical simulation models are set up with the target of investigating the meshing, element activation and variation of process parameters. Appropriate discretization of WAAM components is found to be a major problem when setting up a simulation. The meshing of the component is limited by the element type and size and the meshing routines used. Also, differences in the axes of motion for the simulation and the real process cause the simulation to differ from reality. High element start temperatures are found to be beneficial for simulation stability and performance. An integrated parameter variation was made possible with the modeling techniques used. Full article

The mechanical properties of metals produced by Wire Arc Additive Manufacturing (WAAM) differ significantly from those of rolled sheets due to their cast-like structure and repeated thermal cycling. This study aims to develop a predictive model capable of accurately estimating the stress–strain behavior of deposited metal based on process parameters. To achieve this, a series of experiments were conducted, and test specimens were produced. Arc current and deposition rate were selected as factors in a quasi-D-optimal experimental design. Tensile test data were analyzed using the least squares method, resulting in the derivation of regression equations that relate the stress–strain characteristics to the deposition parameters. To verify that the location of specimen extraction does not influence the test results, both thermal modeling and metallographic analysis were employed. Three key findings were established: (1) Thermal simulations and metallographic observations indicate that after the deposition of the first 5–6 layers, the microstructure becomes relatively similar; (2) significant microstructural variation occurs only in the final layer; and (3) six new regression equations were developed to predict the mechanical properties of the deposited metal based on WAAM process parameters. Full article

TiB₂ and TiC particles were separately introduced to modify the Al-Mg-Si alloy fabricated by wire-arc additive manufacturing (WAAM) to solve the problem of hot cracking. The results showed that modification of the Al-Mg-Si alloy with TiB₂ or TiC particles completely suppressed the hot cracks found in commercial Al-Mg-Si alloys fabricated by WAAM due to the transformation from columnar grains to fine equiaxed grains with a mean diameter of approximately 10 μm. The ultimate strength and yield strength of the as-deposited Al-Mg-Si/TiB₂ (AD-TB) and Al-Mg-Si/TiC (AD-TC) alloys were similar, but the elongation of the latter one was higher due to its low porosity. The ultimate strength (353.7 ± 5.0 MPa) and yield strength (309.7 ± 1.9 MPa) of the heat-treated Al-Mg-Si/TiC (HT-TC) alloy was significantly higher than those (300.8 ± 2.7 MPa and 256.2 ± 2.8 MPa, respectively) of the heat-treated Al-Mg-Si/TiB₂ (HT-TB) alloy. The fatigue resistance of the HT-TC was better than that of the HT-TB due to less porosity and a more uniform distribution of TiC particles in the HT-TC alloy. Full article

In the context of growing environmental concerns and the demand for more sustainable manufacturing practices, this study evaluates the environmental and economic performance of two production routes for a stainless steel support block used in steel mills. A comparative Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) were conducted to assess a conventional subtractive manufacturing process based on Computer Numerical Control (CNC) machining versus a hybrid approach that combines Plasma Arc-Wire Arc Additive Manufacturing (PA-WAAM) with CNC finishing. The LCA was carried out using ReCiPe 2016 Midpoint and Endpoint methodologies in SimaPro, while the LCC employed a cradle-to-gate cost model. Results showed that the hybrid WAAM-CNC route reduced average environmental impacts by 49% across 18 categories and decreased steel consumption by approximately 70% due to near-net-shape fabrication. Although the hybrid method incurred an approximate 3.5 times increase in unit production cost, this was primarily attributed to equipment investment. In contrast, operational costs such as labor, materials, and consumables were significantly lower—by 66%, 28%, and 45%, respectively. These findings support the hybrid approach as a more sustainable manufacturing alternative with the potential for long-term cost optimization as additive technologies mature. Full article

This study investigates the influence of varying layer thickness through interlayer machining in Wire Arc Additive Manufacturing (WAAM) and its impact on microstructural evolution, mechanical properties, and residual stress distribution. It compares four types of WAAM samples: As-built with uneven layer thickness without interlayer machining and uniform layer thicknesses of 2 mm, 1.5 mm, and 1 mm achieved through interlayer machining. As-built components exhibited coarse columnar grains and uneven deposition, adversely affecting hardness and strength. Interlayer machining at reduced layer thickness refined grains, restricted growth, and induced plastic deformation, leading to enhanced mechanical properties. Grain refinement achieved reductions of 62.7% (top), 77.6% (middle), and 64.3% (bottom), significantly improving microstructural uniformity. Microhardness increased from 150 to 180 HV (as-built) to 210 to 230 HV (machined to maintain 1 mm layer thickness), marking a 40–43% improvement. Tensile strength was enhanced, with UTS increasing from 494.72 MPa to 582.11 MPa (17.6%) and YS from 371 MPa to 471 MPa (26.9%), although elongation decreased from 59% to 46% (22% reduction). Residual stress was reduced by 55–60%, improving structural integrity. These findings highlight interlayer machining as a key strategy for optimizing WAAM-fabricated components while balancing mechanical performance and manufacturing efficiency. Full article

Many countries around the world are in a race against time to decarbonise their energy systems. One of the avenues being explored in detail is Offshore Renewable Energy (ORE), with technologies such as wind, wave, and tidal. All of these technologies are in their infancy within the marine environment and required heavy Research and Development (R&D) to make them commercially viable. With so much demand for these industries, the supply chain is heavily constrained. A solution that has shown great potential to alleviate the pressure on the supply chain is the use of Wire Arc Additive Manufacturing (WAAM) for the use of onsite repair or manufacture for components. This is due to its ability to produce large-scale parts, with low emissions and at a lower cost than other Additive Manufacturing (AM) processes. The opportunity to use this technology could result in shorter downtimes and lead to a reduction in the Levelised Cost of Energy (LCOE). However, knowing that offshore structures are subject to cyclic loading conditions during their operational lifespan, fatigue properties of new materials and manufacturing processes must be well documented and studied to avoid any catastrophic failures. An issue often seen with WAAM is the presence of residual stresses. This study looks at fatigue cracking on Compact Tension C(T) specimens that have undergone laser shock peening and rolling, surface treatment processes that form compressive residual stresses at the surface of the material. In this study, the influence of fatigue overloading on the residual stress distribution in surface-treated WAAM specimens is evaluated and the effectiveness of the post-processing techniques on the subsequent fatigue behaviour is explored. Full article

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths. Full article

Wire arc additive manufacturing (WAAM) is a viable technology for manufacturing complex and medium-to-large-sized invar alloy components. However, the cyclic thermal input during the WAAM process may cause the austenite grains in the component to grow abnormally, adversely impacting the material’s mechanical properties. The addition of alloying elements such as Cr, Mo, and V can refine the microstructure of invar alloy to solve these problems. This study examines the influence of Cr, Mo, V, and N on the microstructure and mechanical properties of invar alloy produced through wire arc additive manufacturing. The elements Cr, Mo, and V can form various carbides and nitrides in invar alloys. These precipitation phases are distributed in various forms at grain boundaries and inside the grain, which can refine both the grain and the cellular substructure inside the grain. Moreover, these precipitation phases are distributed in different forms, impeding dislocation movement, thereby enhancing the strength of the invar alloy. The mean tensile strength of WAAM-fabricated high-strength invar alloy in this study attained 793 MPa, approximately 99% higher than that of ordinary invar alloy. The mechanical anisotropy of WAAM-fabricated invar alloy can be ascribed to the thermal interactions between adjacent deposition units. Full article

Wire and arc additive manufacturing (WAAM) stands out from other deposition techniques for being able to produce bigger parts and with higher deposition rates. However, due to the high thermal input, it is necessary to carefully select the deposition strategy and parameters to achieve good geometry, low defects and adequate mechanical properties. As a recent technology, different studies have been developed comprehending the deposition approach, aiming to achieve parts with specific characteristics, usually evaluating the geometry, microstructure and mechanical properties, such as yield and tensile strengths, residual stresses and microhardness; however, the last is usually presented by mean values, requiring more details to comprehend its behavior further. In this sense, this work aims to evaluate the microhardness variation on walls of ER70S-6 deposited by WAAM-CMT in detail, with different deposition strategies, unidirectional and bidirectional, and with and without interlayer temperature control. The wall’s geometry was also assessed in terms of height and width. The results showed that both bidirectional deposition and temperature control contributed to improving the wall’s geometry. Combining methods led to a 26% increase in the wall width and 9% in the height; combining both methods also led to a more homogeneous distribution of microhardness throughout the wall with less than 15 HV variation. For all the deposition strategies, the wall region influenced the microhardness, and relatively higher values were obtained on the upper region of the wall, followed by the central and lower regions. Full article

This paper reviews the potential of Wire Arc Additive Manufacturing (WAAM) for architecture. It uniquely addresses its feasibility by evaluating existing large-scale, real-world prototypes developed to date and compiling critical gaps identified in the literature. Although previous review papers concerning WAAM for architecture exist, they focus on the technical aspects of the technology, such as the mechanical properties, defects, and process parameters. No existing review analyzes which architectural applications are being implemented nor the scale and degree prototyping accomplished for each application. WAAM, a form of metal additive manufacturing using an electric arc to melt and deposit wire, offers unique advantages for the construction industry. It allows for high deposition rates, structural integrity, and cost-efficiency using steel. However, challenges such as producing large-scale components and limited design freedom and lower resolution compared to other additive manufacturing processes remain. This review first contextualizes WAAM within the broader landscape of additive manufacturing technologies for construction and examines its proposed architectural applications, such as steel connections, columns, trusses, and bridge elements. This study emphasizes the need for real-world experimentation through large-scale prototypes to assess the practicality and scalability of WAAM in architecture. The results of this study reveal that 36 architectural projects using WAAM exist in the literature, whose application range from structural (such as beams, columns, and nodes) to nonstructural components (such as facades and ornamental elements). Based on these, a classification for WAAM in architecture is proposed: (1) stand-alone WAAM structures, (2) printed connector pieces to join standard steel parts, and (3) reinforcement for conventional steel elements using WAAM. The size of typical functional prototypes to date averages 200 × 200 × 200 mm, with exceptional cases such as the diagrid column of 2000 mm height and the MX3D Bridge, which spans over 12 m. A detailed analysis of seven projects documents the scale and development of the prototypes, functional lab configuration, and process parameters. Through this review, the current technical feasibility of WAAM in architecture is established. Full article

Dot-by-dot Wire and Arc Additive Manufacturing (WAAM) is a promising technique for producing large-scale lattice structures, offering significant benefits in terms of deposition rate and material utilization. This study explores strategies for fabricating bar intersections using the dot-by-dot WAAM technology, focusing on creating robust and predictable structures without requiring parameter modifications or real-time monitoring during the deposition. Two different deposition strategies were proposed, that can be, at least geometrically, applied to a general intersection with multiple bars with different angles. In this work such strategies were only experimentally tested on two-bar intersections, assessing their performance in terms of geometrical accuracy, symmetry, and material efficiency. Strategies which utilize layer-by-layer deposition with multiple overlapping dots, called B here, demonstrated the best results in terms of the geometrical features in the intersection zone, assessed by different metrics obtained through an analysis of pictures, such as low asymmetry and high material volume in the intersection zone. In addition, the findings suggest that removing cooling pauses during the deposition of multiple dots on the same layer slightly improves the joint by minimizing excess material buildup. The proposed approach offers a scalable framework for optimizing intersection deposition, paving the way for improved large-scale metal lattice structure manufacturing. Full article

This study investigates the machining parameters that affect the surface roughness of additively manufactured specimens employing wire arc additive manufacturing (WAAM) using electric arc welding as a heat source. The specimens were prepared using E6013 and E7018 filler rods for layered deposition on a mild steel base plate. For the machining operation, two variable parameters, cutting speed and depth of cut, were selected and coded as high (480 RPM, 0.5 mm depth) and low (310 RPM, 0.25 mm depth) while keeping the feed rate constant. The study employed a 2^k factorial design of experiment (DOE) using Minitab software to assess the impact of parameters and their levels on the output response of surface roughness. Analysis of variance (ANOVA) results show that cutting parameters like cutting speed and their interaction with the depth of cut significantly affect surface quality. The experimental data were also used to develop polynomial model response equations for predicting surface roughness. This study firmly demonstrates the critical role of machining parameters in enhancing the surface quality of low-cost additively manufactured components using an electric arc welding heat source. Full article

The accurate prediction of weld bead geometry is crucial for ensuring the quality and consistency of wire and arc additive manufacturing (WAAM), a specific form of directed energy deposition (DED) that utilizes arc welding. Despite advancements in process control, predicting the shape and dimensions of weld beads remains challenging due to the complex interactions between process parameters and material behavior. This paper addresses this challenge by exploring the application of symmetrical neural networks to enhance the accuracy and reliability of geometric predictions in WAAM. By leveraging advanced machine learning techniques and incorporating the inherent symmetry of the welding process, the proposed models aim to precisely forecast weld bead geometry. The use of neuronal networks and experimental validation demonstrate the potential of symmetrical neural networks to improve prediction precision, contributing to more consistent and optimized WAAM outcomes. Full article

This study investigates the predictive modelling of weld bead geometry in wire arc additive manufacturing (WAAM) through advanced machine learning methods. While WAAM is valued for its ability to produce large, complex metal parts with high deposition rates, precise control of the weld bead remains a critical challenge due to its influence on mechanical properties and dimensional accuracy. To address this problem, this study utilized machine learning approaches—Ridge regression, Lasso regression and Bayesian ridge regression, Random Forest and XGBoost—to predict the key weld bead characteristics, namely height, width and cross-sectional area. A Design of experiments (DOE) was used to systematically vary the welding current and travelling speed, with 3D weld bead geometries captured by laser scanning. Robust data pre-processing, including outlier detection and feature engineering, improved modelling accuracy. Among the models tested, XGBoost provided the highest prediction accuracy, emphasizing its potential for real-time control of WAAM processes. Overall, this study presents a comprehensive framework for predictive modelling and provides valuable insights for process optimization and the further development of intelligent manufacturing systems. Full article