Establishing optimal friction stir welding parameters for AA2219-T87 Al-alloy using comprehensive RSM and GA approach

Abstract

Abstract AA2219-T87 aluminium alloy has been used in aerospace applications because of its high strength, low density and resistance to corrosion. The copper in the alloy improves the hardness and lowers melting point, which makes two sections easily joined with a process called friction stir welding of aluminium alloy. In the present work, heat-treated AA2219 alloy was butt welded by solid-state friction stir welding process. This work aims to develop a suitable combination of welding parameters for producing defect-free weld joints of AA2219 alloy to improve tensile and corrosion properties. The most influencing control parameter for optimising the friction stir welding responses was determined using sophisticated design of experiments (DOE) techniques. Ultimate tensile strength and corrosion resistance are observed as responses in this study. To achieve the desired weld responses, a three-factor, three-level Box-behneken design was used. Analysis of Variance (ANOVA) was carried out to examine the interaction effect and significant welding parameter to set the optimal level of welding conditions. Multi-response regression equations have been developed using response surface methodology (RSM) to estimate the output characteristics of weld. The Genetic algorithm (GA) was used to optimise the predicted mathematical model under given optimization constraints. The results shown that the optimum responses are obtained at input factors rotational speed 300 rpm, welding speed 80 mm min−1, and axial force of 10kN.