Abstract
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.
Highlights
Combined optimization of welding process parameters and the welding sequence is needed to mitigate distortion produced during welding
Sulaiman et al [6] studied the effect of welding parameters, current, voltage, speed, wire feed, and shielding gas on distortion produced in T and butt-jointed steel plates
An effort has been made to combine the weld parameter an devised in this research gives approach forof weld distortion sequence optimization in aa comprehensive framework
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. During the last step of optimization, i.e., GA-based optimization, only one weld sequence was used, and the focus of the research was to find the optimum process parameters It took 75 weld simulations to achieve the required goal. It is not feasible to search for optimum weld parameters along with an optimum weld sequence with the design of experiment approach Other optimization techniques, such as GA and Artificial Neural Networks, have been used by various researchers. A framework is proposed to minimize welding induced distortion by finding a combination of the optimum weld parameters and optimum weld sequence It is a sequential approach in which optimum weld parameters are selected using the response surface method. The framework of the complete optimization process is discussed
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