Process Parameter Optimization in Friction Stir Spot Welding of High-density Polyethylene Sheets Using GA, PSO, and ABC Algorithm

Abstract

AbstractThe promising applications of high-density polyethylene (HDPE) in automotive and aerospace industries demand for more reliable and durable fabrication techniques. Friction stir spot welding is one such fabrication process which has proved to be a favorable joining technique for HDPE. In this paper, mathematical model has been developed using response surface methodology (RSM) for the friction stir spot welding (FSSW) process on commercial 4 mm HDPE sheets. The welding parameters, namely tool rotational speed, axial feed rate, plunging depth, and dwell time, were taken as decision variables for the resulting joint properties, namely the lap shear strength (LSS) and the temperature variations, are checked across the weld based on these parameters. The equations developed for LSS from experimental results with the help of RSM were used as objective function for the meta-heuristic optimization algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC) algorithm individually. The global optimum that has been deduced from GA, PSO, and ABC algorithm has come out to be consistent for LSS.KeywordsFSSWHDPEProcess parametersMeta-heuristic algorithmsLap shear strength