Springback Reduction in Tailor Welded Blank with High Strength Differential by Using Multi-Objective Evolutionary and Genetic Algorithms

Abstract

The springback behavior on two sides of TWIP (twinning-induced plasticity) and mild steels tailor welded blank (TWB) is considerably different due to the large difference in strength. To reduce springback defects in a U-draw bending process of such TWB, different non-constant blank holding force (BHF) profiles on two sides of the blank are applied in this study. A systematic approach to obtain optimal BHF-stroke profiles, which helps to reduce the springback is proposed. Control of the variable BHF aims at increasing the uniformity in through-thickness of the stress component along the stretching direction, while decreasing the risk of failure due to over-stretching. Therefore, the optimal condition would require satisfying two conflicting objectives simultaneously: (i) minimize springback deformation and (ii) minimize the forming severity, leading to a Pareto-optimal problem. The optimization procedure consists of sampling design, finite element (FE) simulations, metamodeling, and finally the calculation of a Pareto-frontier. Generated outputs from FE simulations on statistically significant sampling points are used for the construction of metamodels of optimum accuracy and complexity, which, in turn, are used to evaluate the output for any set of inputs, replacing the computing intensive FE simulations. A novel genetic algorithms based multi-objective optimization technique is subsequently applied for optimization.