Welding induced distortion causes dimensional inaccuracies in parts being produced and assembly fit-up problems during manufacturing. In this study, a framework is proposed to mitigate weld distortion at the design stage. A sequential approach is adopted to optimize the welding process. In the first phase, welding process parameters are optimized through the response surface method. The effect of these parameters on the overall distortion of the welded part is observed by a simulation of the welding process. In the second phase, the weld sequence is optimized using the optimum weld parameters. A reinforcement learning-based Q-learning technique is used to select the optimum welding path by sequential observation of weld distortion at each segment being welded. The optimum process parameters and weld path sequence have been selected for 3 mm steel plates having a lap joint configuration and a 2 mm vent panel with a butt joint configuration. It is concluded that the combination of the optimum welding parameters and welding sequence yields minimum distortion. By applying this framework, a reduction of 19% is observed in overall welding induced distortion.
Distortion and residual stress are two unwelcome byproducts of welding. The former diminishes the dimensional accuracy while the latter unfavorably affects the fatigue resistance of the components being joined. The present study is a multi-objective optimization aimed at minimizing both the welding-induced residual stress as well as distortion. Current, voltage, and welding speed were the welding parameters selected. It was observed that the parameters that minimize distortion were substantially different from those that minimized the residual stress. That is, enhancing dimensional accuracy by minimizing distortion results in an intensification of residual stresses. A compromise between the two objectives was therefore necessary. The contour plots produced from the response surfaces of the two objectives were overlaid to find a region with feasible parameters for both. This feasible region was used as the domain wherein to apply the novel butterfly optimization algorithm (BOA). This is the first instance of the application of the BOA to a multi-objective welding problem. Weld simulation and a confirmatory experiment based on the optimum weld parameters thus obtained corroborate the efficacy of the framework.
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