Optimization of concurrent criteria in the stamping process

One of the hottest challenges in automotive industry focuses on weight reduction in sheet metal forming operations, in order to produce a high quality metal part with minimal cost production. Stamping is the most widely used sheet metal forming process; but its implementation introduces several difficulties such as springback and failure. A global and simple approach to circumvent these unwanted process drawbacks consists in optimizing the process parameters with innovative methods. The aim of this paper is to prevent and predict these two phenomena. For this purposed, the simulation of the stamping of an industrial work piece is investigated to estimate the springback and the failure. To optimize this two criteria, a global approach was chosen. It's the Simulated Annealing algorithm hybridized with the Simultaneous Perturbation Stochastic Approximation in order to gain in time and in precision. Although, the optimization of stamping problem is multi-objective and accurately springback and failure are two conflicting criteria. To solve this kind of problems, Normal Boundary Intersection and Normalized Normal Constraint Method are two methods for generating a set of Pareto-optimal solutions with the characteristic of uniform distribution of front points. Performing test problems with comparison of Non-dominated Sorting Genetic Algorithm II results, the accuracy of presented algorithms is investigated. The results show that the proposed approaches are efficient and accurate in most cases.