Search Results (295)

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

MIL-STD-1530D and the United States Air Force (USAF) Structures Bulletin EZ-SB-19-01 require an ability to predict the growth of naturally occurring three-dimensional cracks with crack depths equal to what they term an equivalent initial damage size (EIDS) of 0.254 mm. This requirement holds for both additively manufactured and conventionally built parts. The authors have previously presented examples of how to perform such predictions for additively manufactured (AM) Ti-6Al-4V; wire arc additively manufactured (WAAM) 18Ni 250 Maraging steel; and Boeing Space, Intelligence and Weapon Systems laser bed powder fusion (LPBF) Scalmalloy^®, which is an additively manufactured Aluminium-Scandium-Mg alloy, using the Hartman-Schijve crack growth equation. In these studies, the constants used were as determined from ASTM E647 standard tests on long cracks, and the fatigue threshold term in the Hartman-Schijve equation was set to a small value (namely, 0.1 MPa √m). This paper illustrates how this approach can also be used to predict the growth of naturally occurring three-dimensional cracks in WAAM CP-Ti (commercially pure titanium) specimens built by Solvus Global as well as in WAAM-built Inconel 718. As in the prior studies mentioned above, the constants used in this analysis were taken from prior studies into the growth of long cracks in conventionally manufactured CP-Ti and in AM Inconel 718, and the fatigue threshold term in these analyses was set to 0.1 MPa √m. These studies are complemented via a prediction of the growth of naturally occurring three-dimensional cracks in conventionally built M300 steel. Full article

The increasing demand for smaller batch sizes and mass customisation in production poses considerable challenges to logistics and manufacturing efficiency. Conventional methodologies are unable to address the need for expeditious, cost-effective distribution of premium-quality products tailored to individual specifications. Additionally, the reliability and resilience of global logistics chains are increasingly under pressure. Additive manufacturing is regarded as a potentially viable solution to these problems, as it enables on-demand, on-site production, with reduced resource usage in production. Nevertheless, there are still significant challenges to be addressed, including the assurance of product quality and the optimisation of production processes with respect to time and resource efficiency. This article examines the potential of integrating digital twin methodologies to establish a fully digital and efficient process chain for on-site additive manufacturing. This study focuses on wire arc additive manufacturing (WAAM), a technology that has been successfully implemented in the on-site production of naval ship propellers and excavator parts. The proposed approach aims to enhance process planning efficiency, reduce material and energy consumption, and minimise the expertise required for operational deployment by leveraging digital twin methodologies. The present paper details the current state of research in this domain and outlines a vision for a fully virtualised process chain, highlighting the transformative potential of digital twin technologies in advancing on-site additive manufacturing. In this context, various aspects and components of a digital twin framework for wire arc additive manufacturing are examined regarding their necessity and applicability. The overarching objective of this paper is to conduct a preliminary investigation for the implementation and further development of a comprehensive DT framework for WAAM. Utilising a real-world sample, current already available process steps are validated and actual missing technical solutions are pointed out. Full article

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