Multi-objective optimization of VBHF in sheet metal deep-drawing using Kriging, MOABC, and set pair analysis

The optimization of variable blank holder force (VBHF) in sheet metal deep-drawing has important significance in improving forming part quality. This paper proposed a new multi-objective VBHF optimization method to reduce the tearing, wrinkling, and springback in the drawing process. The influence mechanism of springback on forming precision is analyzed and a new evaluation criterion of springback is developed. Sidewall wrinkling is taken into account to quantify the wrinkling. Three quality evaluation criteria for ellipsoid forming part are established and a VBHF optimization model in deep-drawing is formulated by cooperated Kriging approximate model with three defects. Multi-objective artificial bee colony (MOABC) algorithm is employed to get VBHF Pareto-optimal set from the VBHF Kriging mode. Set pair analysis (SPA) is applied to select the best solution in Pareto set. An example of the head-type part deep-drawing is used to illustrate the method. The experimental results show that the VBHF multi-objective optimization problem can be solved well by proposed method.