Finite element method (FEM) simulations are a powerful tool for understanding the thermal–metallurgical–mechanical effects of wire arc additive manufacturing (WAAM). Nonetheless, owing to the multiphysical nonlinear nature of welding coupled with the longer deposition time of WAAM, FEM simulations can be laborious and time-consuming, which makes it difficult to simulate the numerous procedural parameters of WAAM. Therefore, the present work aimed to employ an FEM mode to analyze the influence of idle time (30–240 s) on the interpass temperature (IT) of 20-layer single-bead walls produced via WAAM and use the FEM results to develop a predictive model for the IT based on an artificial neural network (ANN). The FEM simulations were performed using a heat source and a 20-layer single-bead wall model that was experimentally calibrated and validated. The first layers exhibited similar energy accumulation; however, as the wall height increased, the IT rapidly increased under to low idle times (≤120 s). The ANN was trained using the FEM simulations results, validated with FEM results (not included in the training database), and used to establish a process map (including the idle time, number of layers, and IT). This can help the manufacturers to obtain a suitable balance between productivity (lower idle times) and part behavior (e.g., microstructure and mechanical properties).

Prediction of the interpass temperature of a wire arc additive manufactured wall: FEM simulations and artificial neural network

Characteristics of welding distortion and residual stresses in thin-walled pipes by solid-shell hybrid modelling and experimental verification

Welding sequence optimization to reduce welding distortion based on coupled artificial neural network and swarm intelligence algorithm

The fabrication of components involves the deposition of multiple beads in multiple layers for wire-arc additive manufacturing (WAAM). WAAM performed using gas metal arc welding (GMAW) allows for the manufacturing of parts through multiple-bead multi-layer deposition, which depends on the process variables. Thus, the selection of process parameters along with their required levels is mandatory to deposit multiple layers for WAAM. To obtain the desired levels of parameters, bead-on-plate trials were taken on the base plate of low alloy steel by following an experimental matrix produced through the Box–Behnken design (BBD) on GMAW-based WAAM. Wire feed speed, travel speed, and voltage were chosen as the input parameters and bead width and bead height were chosen as the output parameters. Furthermore, the robustness and adequacy of the obtained regression equations were analyzed by using analysis of variance (ANOVA). For both responses of BW and BH, values of R2 and adj. R2 were found to be near unity, which has shown the fitness of the model. Teaching–learning-based optimization (TLBO) technique was then employed for optimization. Within the selected range of process variables, the single-objective optimization result showed a maximum bead height (BH) of 7.81 mm, and a minimum bead width (BW) of 4.73 mm. To tackle the contradicting nature of responses, Pareto fronts were also generated, which provides a unique non-dominated solution. Validation trials were also conducted to reveal the ability and suitability of the TLBO algorithm. The discrepancy between the anticipated and measured values was observed to be negligible, with a deviation of less than 5% for all the validation trials. This demonstrates the success of the established model and TLBO algorithm. The optimum feasible settings for multi-layer metal deposition were determined after further tuning. A multi-layer structure free from any disbonding was successfully manufactured at the optimized variables. The authors suggest that the optimum parametric settings would be beneficial for the deposition of layer-by-layer weld beads for additive manufacturing of components.

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Optimization of Bead Morphology for GMAW-Based Wire-Arc Additive Manufacturing of 2.25 Cr-1.0 Mo Steel Using Metal-Cored Wires

The prospect of using metal-cored wires instead of solid wires during gas metal arc welding (GMAW) of 2.25 Cr–1.0 Mo steels embraces several challenges. The in-service requirements for the equipment made up of these steels are stringent. The major challenge faced by the manufacturers is temper embrittlement. In the current study, the temper embrittlement susceptibility of the welded joint was ascertained by subjecting it to step cooling heat treatment. A 25 mm thick 2.25 Cr–1.0 Mo weld joint was prepared using a combination of the regulated metal deposition (RMD) and GMAW processes incorporating metal-cored wires. After welding the plates were exposed to post-weld heat treatment followed by a rigorous step cooling heat treatment prescribed by API standards. The temper embrittlement susceptibility of the weld joint was ascertained by Bruscato X-factor as well as by formulating ductile-to-brittle transition temperature (DBTT) curves by carrying out the impact toughness testing at various temperatures. Detailed microscopy and hardness studies were also carried out. It was established from the study that the X-factor value for the welded joint was 15.4. The DBTT for the weld joint was found to occur at −37 °C which was well below 10 °C. Optical microscopy and scanning electron microscopy indicated the presence of carbides and the energy dispersive X-ray spectrometry studies indicated the presence of chromium and manganese-rich carbides along with the presence of sulfur near the grain boundaries. This study establishes a base for the usage of metal-cored wires particularly in high temperature and pressure application of Cr–Mo steels.

Elucidating the Effect of Step Cooling Heat Treatment on the Properties of 2.25 Cr-1.0 Mo Steel Welded with a Combination of GMAW Techniques Incorporating Metal-Cored Wires.

Cristian Rubio-Ramirez

Papers

Prediction of angular distortion due GMAW process of thin-sheets Hardox 450® steel by numerical model and artificial neural network