Implementation of hybrid RSM-GA optimization techniques in underwater friction stir welding

Abstract

Standard friction stir welding process parameters have a considerable impact on the quality of functional parts produced by underwater friction stir welding (UWFSW) with additive water. Hybrid statistical techniques may be used to optimize operating parameters in order to improve the aim function. The tensile strength (UTS)of parts fabricated with UWFSW by Al 6063 material in accordance with ASTMD638-14 tests is investigated in this study. In the construction of test specimens, three parameters were varied: rotational speed from 1000 to 1800 rpm, travel speed from 4 to 10 mm/s, and shoulder diameter from 10 to 20 mm. The response surface methodology (RSM) based central composite design (CCD) matrix for the parametric combination was constructed using a second-order polynomial fitting model. The maximum UTS of testing samples on the 201T universal testing machine (UTM) was 208.27 MPa. These process parameters are also optimized using hybrid optimization approaches such as response surface methodology- genetic algorithm (RSM-GA). RSM-GA had the highest precision of 98.99 percent, which resulted in optimal characteristics such as rotating speed 1800 rpm, travelling speed 4 mm/s, and shoulder diameter 15 mm, which resulted in a maximum tensile strength of 199.0212 MPa.