Multi-Objective Optimization of Friction Stir Spot-Welded Parameters on Aluminum Alloy Sheets Based on Automotive Joint Loads

Abstract

By controlling various friction stir spot-welded (FSSW) factors, two base sheets AA 5052-H32 and 6061-T6 were selected to bond similar and dissimilar metal joints while considering dissimilar configuration orders. The effects of weld parameters on the sheer strength and peel strength were separately developed into empirical models utilizing the integrated central composite matrix design and response surface methodology (RSM). Meanwhile, the finite element (FE) analysis of the multi-axis load-bearing characteristics for automotive solder joints during service was carried out. As a result, the weights of the shear and axial stress, accounting for 90.5% and 9.5% respectively, were employed to restrict the relationship between multiple target properties, and the resulting security strength was applied to determine the feasible domain in subsequent parametric optimization. In order to enable the optimal multi-axis capacities in accordance with the load mode, the genetic algorithm NSGA-II was chosen to compute the Pareto front and further determine the best compromise solutions. The obtained optimums corresponding to each joining condition were validated by confirmation runs, indicating that this coupled multi-objective optimization approach based on working conditions was beneficial to the targeted improvement of post-weld mechanical properties.

Keywords

• friction stir spot weld
• process parameter
• multi-objective optimization
• automotive joint loads