Mechanical and Microstructure analysis of ER410 stainless steel processed by wire arc additive manufacturing (WAAM)

Cold metal transfer (CMT)–based wire-arc additive manufacturing (WAAM) is increasingly popular for the production of large and complex metallic components due to its high deposition rate, low heat input, and excellent material efficiency. The accurate prediction of the bead geometry is of great importance to enhance the stability of the process and its dimensional accuracy. Besides the wire feed speed (WFS) and travel speed (TS), the interlayer temperature is another key factor in determining the bead geometry because of the heat accumulation in the multilayer deposition. In this paper, considering the varying interlayer temperature, WFS, and TS as inputs, an artificial neural network (ANN) is developed to predict the bead width, height, and contact angle; then, by connecting the ANN model with a bead geometric model, a combined model is established to improve the ANN model. Based on experimental test data, with random combinations of input parameters, the combined model is demonstrated to be able to accurately predict the bead geometry (mean error < 5.1%). The general effect of interlayer temperature on the bead geometry was also investigated by experiment.

Wire Arc Additive Manufacturing (WAAM) is a metallic additive manufacturing process based on the fusion of metallic wire using an electric arc as a heat source. The challenge associated with WAAM is heat management and understanding bead geometry. The printing process involves high temperatures, which results in the build-up of residual stresses can often cause deformations in a component. All of the process variables, such as torch speed (TS), wire feed speed (WFS), idle time, combine to produce the geometry of the deposit bead that results in the desired component shape. So, determining a method for choosing a good combined parameter process is very important to obtain a high-quality part. This article presents a study on how to use the WAAM process to produce a complexity part of aluminium alloys. The step of the determination process parameter is concentrated to develop in this study. An experimental design is determined to study the influence between the process parameters, for example, WFS, TS, high layer, length of bead. Different samples are made using the Yaskawa robot, using the classic CMT (Cold Metal Transfer) as a manufacturing method, using zigzag filling as a manufacturing strategy with the same WFS and same idle times and different TS, different bead lengths. A new manufacturing method using the zigzag filling strategy is proposed by adding an important step in determining the process parameters. The results indicate that the length of the bead has a significant impact on another parameter of the process.

Additive manufacturing is a very popular word in the present day as various researchers are focused on this field all around the world. Every new researcher coming to this field of additive manufacturing is busy in developing new methods and techniques to make it more versatile and efficient in terms of applicability. Wire arc additive manufacturing (WAAM) process, a new addition to the AM processes, is growing rapidly in the field of the metal additive manufacturing process because of its high deposition rate, low equipment cost compared to laser and electron beam, saving lead time, high BTF (buy-to-fly) ratio, no limit on part size, and many other advantages. In this study, a wire arc additive manufacturing system based on cold metal transfer gas metal arc welding technology was used to fabricate a solid block component with ER70S6 MS alloy welding wire. This study presents the investigation on anisotropy behavior of resulted microstructure and mechanical properties including tensile, impact, and hardness of the manufactured block component. The samples were taken along the parallel and perpendicular to the welding direction. The tensile properties of the samples were found almost uniform in both the directions with values of the ultimate tensile strength (UTS), yield strength (YS), and elongation (%E) found to be 510 ± 5 MPa, 373 ± 5 MPa, and 37% ± 2%, respectively. The average Vickers hardness values at 10 kg load in parallel and perpendicular directions were found around 80 and 72 kg/mm2. The impact toughness at −30℃ was found to be 148 and 170 J in the parallel and perpendicular direction. The toughness obtained is much higher than the required minimum impact strength of 80 J at the subzero temperature as per the AWS requirement for the used ER70S6 welding wire. The microstructure observed in welded samples is ferrite and bainite which consists inside and along the prior austenite grain boundaries. Mostly grains were elongated in the welding direction. From the present work, it is evident that the near-net-shape component fabricated with the WAAM process has quite acceptable mechanical properties without much effect of directionality.

Wire Arc Additive Manufacturing (WAAM) is an additive manufacturing process that uses an electric arc as the heat source to melt the feed metal wire and deposit it as per the desired 3D shapes. The current study investigates the influence of critical process parameters, namely welding current and travel speed, on the bead geometry and microstructure of deposits of stainless steel (308L). The results reveal that higher welding currents lead to increased bead width, while travel speed inversely affects bead height. Moreover, contact angles between the deposited material and the substrate increase with the welding current. An analysis of the liquid-to-vapor transition (δ) highlights its correlation with travel speed, impacting the spreadability of the deposited material. Notably, among all tested combinations of current and travel speed, 120 A and 25 mm/min yield uniform layer deposition of 308L stainless steel wire, an ideal outcome for WAAM applications. Additionally, it was observed that the percentage of the ferrite phase within the deposited material’s microstructure exhibits an intriguing relationship, increasing with travel speed while decreasing with rising current and layer number. These findings offer valuable insights into process optimization for WAAM-based orthopedic applications, emphasizing the potential for customized orthopedic knee implants with improved quality and performance.

The usage of additive manufacturingAdditive manufacturing as a process for component production is becoming increasingly important, as it offers enormous potential for material savings and therefore cost reduction. In particular, Wire Arc Additive ManufacturingWire-arc additive manufacturing (WAAM) processes are arousing a great deal of interest in several industries by its high deposition rates at low equipment acquisition costs and the low buy-to-fly ratio. This process is being specifically investigated for aerospace and space applications, as it allows the production of large structural complex near-net-shape components in small batches. However, a major drawback of this technology is the high anisotropic behaviour of the manufactured structures in the as-welded state. Since the Ni–Fe alloy Inconel 718Inconel 718 is an anisotropic material, in which introduced textures strongly influence the mechanical propertiesMechanical properties, the impact of the WAAM processing route on the mechanical propertiesMechanical properties as well as the underlying microstructureMicrostructures is specifically focused on in this study. Using a plasma arc as heat source and Inconel 718Inconel 718 wire as feedstock material, test walls are produced in order to characterize the created material. In addition to the identification of factors influencing the process, temperature cycles are measured at different positions during the build-up. The resulting microstructureMicrostructures is subsequently evaluated macroscopically as well as microscopically and examined regarding pores and precipitates. SEM/EDS analysis is carried out to investigate the underlying microstructureMicrostructures of the additively manufactured parts. Furthermore, mechanical propertiesMechanical properties are evaluated in the build-up direction as well as transversal to this direction in order to characterize the anisotropyAnisotropy of the material.

Objectives: Fabrication of a cylinder-shaped High-Strength Low Alloyed steel wall component through wire (metal cored) arc additive manufacturing and assess the homogeneity and integrity of the built component. Method: Mechanical testing and microstructural characterizations such as optical microscopy, scanning electron microscopy and electron backscattered diffraction techniques were performed at distinct regions (namely, bottom and top). Findings: The conducted tensile test at the bottom area recorded a tensile strength of 864 MPa, which is 5.9 % higher than the top region but with a lower total elongation. The microhardness study revealed that the average hardness at the bottom region was 266 HV0.5, while the top region was 241 HV0.5. The microstructural analysis conducted in both areas indicates that the bottom region exhibits better hardness and strength due to the presence of a high value of geometrically necessary dislocations, High-Angle Grain Boundaries and increased grains with reduced size. However, the built component proves to have better homogeneity with marginal deviations in the properties estimated. Novelty: Solid wire was used as a predominant filler material for the Wire-Arc Additive Manufacturing (WAAM) process, which requires high heat input to melt the material. Hence, to reduce the heat input, metal-cored wire was used instead of solid wire for the Gas Metal Arc -WAAM process. Keywords: Gas metal arc welding, Metal cored wire, Mechanical properties, Direct energy deposition, Wire-arc additive manufacturing

In the wire arc additive manufacturing (WAAM) process, the geometry of single welding beads has significant effects on the stability process and the final quality and shape of manufactured parts. In this paper, the geometry of single welding beads of 308L stainless steel was predicted as functions of process parameters (i.e. welding current I, voltage U, and travel speed v) by using the response surface methodology (RSM). A set of experimental runs was carried out by using the Box-Behnken design method. The adequacy of the developed models was assessed by using an analysis of variance (ANOVA). The results indicate that the RSM allows the predictive models of bead width (BW) and bead height (BH) to be developed with a high accuracy: R2-values of BW and BH are 99.01% and 99.61%, respectively. The errors between the predicted and experimental values for the confirmatory experiments are also lower than 5% that again confirms the adequacy of the developed models. These developed models can efficiently be used to predict the desirable geometry of welding beads for the adaptive slicing principle in WAAM.

Wire arc additive manufacturing of a novel ATZM31 Mg alloy: Microstructure evolution and mechanical properties

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

An economic evaluation of hybrid WAAM-subtractive manufacturing in relation to deposition process parameters

A defect detection system for wire arc additive manufacturing using incremental learning

Droplet transfer behavior in bypass-coupled wire arc additive manufacturing

Laser-CMT (Cold Metal Transfer) arc hybrid additive manufacturing (LHAM) of 316L austenitic stainless steel (316SS) was studied. Surface roughness (R) and the minimum processing margin (dmin) of deposited thin-wall were calculated by the data measured via laser displacement sensor. Microstructure and fracture surface were observed by optical microscope and scanning electron microscope. The scanning speed of LHAM could be increased to 1.2 m/min, 3 times higher than that of wire arc additive manufacturing (WAAM). The R and dmin of LHAMed 316SS were reduced to 40% and 60% of the WAAM, respectively. The microstructure of LHAMed 316SS was composed of columnar or equiaxed grains, which were characterized by δ-ferrite and austenite. The tensile strength of LHAMed sample was higher, but the elongation is lower than that of WAAMed sample because of the formation of the porosity.Laser-CMT (Cold Metal Transfer) arc hybrid additive manufacturing (LHAM) of 316L austenitic stainless steel (316SS) was studied. Surface roughness (R) and the minimum processing margin (dmin) of deposited thin-wall were calculated by the data measured via laser displacement sensor. Microstructure and fracture surface were observed by optical microscope and scanning electron microscope. The scanning speed of LHAM could be increased to 1.2 m/min, 3 times higher than that of wire arc additive manufacturing (WAAM). The R and dmin of LHAMed 316SS were reduced to 40% and 60% of the WAAM, respectively. The microstructure of LHAMed 316SS was composed of columnar or equiaxed grains, which were characterized by δ-ferrite and austenite. The tensile strength of LHAMed sample was higher, but the elongation is lower than that of WAAMed sample because of the formation of the porosity.

Bending fatigue properties of structural steel fabricated through wire arc additive manufacturing (WAAM)

Wire arc additive manufacturing (WAAM), leveraging traditional gas metal arc welding (GMAW) technology, offers a promising approach for fabricating large-scale metallic components with high deposition rates. Among GMAW-based processes, cold metal transfer (CMT) and pulsed metal inert gas (MIG) techniques differ significantly in their metal transfer mechanisms and thermal inputs, which directly influence the resulting material properties. This study systematically compares the microstructural, mechanical, tribological, and corrosion characteristics of 316L stainless steel walls produced using CMT and pulsed MIG WAAM processes under similar heat input conditions (CMT: 323.48 J/mm, pulsed MIG: 329.14 J/mm). The CMT process produced finer grains (11.16 µm) compared to pulsed MIG (14.14 µm), contributing to slightly higher microhardness (171.90 HV versus 171.14 HV) and improved mechanical properties. Charpy impact toughness, yield strength, and ultimate tensile strength were all higher for the CMT process by 16.4%, 3.4%, and 1.3%, respectively, while pulsed MIG showed slightly higher elongation (56% versus 52.25%). Fractographic analysis revealed finer, more uniform dimples in the CMT samples, indicating ductile fracture behavior. In terms of tribological performance, the CMT process exhibited a lower coefficient of friction (0.216 versus 0.249) and a significantly reduced wear-rate (3.4 × 10−3 mm3/m versus 5.5 × 10−3 mm3/m). Corrosion resistance was also marginally better in the CMT samples, with a corrosion rate of 0.05235 mm/year compared to 0.05524 mm/year for pulsed MIG. Overall, the CMT process consistently outperformed pulsed MIG across multiple performance metrics, making it a more favorable choice for high-integrity additive manufacturing of stainless steel components.