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Conference Papers Year : 2013

Concurrent Optimization of Springback and Failure in Stamping Processes


One of the biggest 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 diffi culties 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 this two phenomena. For this purpose, the simulation of the stamping of an industrial workpiece is investigated to estimate the springback and the failure. To optimize this two criteria, a global optimization method was chosen, namely the Simulated Annealing algorithm, hybridized with the Simultaneous Perturbation Stochastic Approximation in order to gain in time and in precision. Indeed, the general optimization of the stamping process is by nature multi-objective and springback and failure are among most used criteria, and they are known to be conflicting.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. We have performed many benchmark problems, and compared the results with those of the NSGA-II Non-dominated Sorting Genetic Algorithm. Then, the comparison was led for the two criteria stamping problem. The results show that the proposed approaches are e fficient and accurate in most cases.
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Dates and versions

hal-00923644 , version 1 (03-01-2014)


  • HAL Id : hal-00923644 , version 1


Fatima-Zahra Oujebbour, Abderrahmane Habbal, Rachid Ellaia. Concurrent Optimization of Springback and Failure in Stamping Processes. 10th World Congress on Structural and Multidisciplinary Optimization WCSMO10, May 2013, Orlando, FL, United States. ⟨hal-00923644⟩
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