Abstract

In high strength sheet metal forming process of body part, crack, wrinkle and severe thinning are the main faults usually. The degree of the faults varies with the change of input process parameters. Optimization for sheet metal forming process of body part is often considered as a multi-objective problem. Design of experiment method and genetic algorithm are often combined together to cope with this multi-objective optimization problem. High strength steel sheet metal forming process is relatively complex and difficult. An intelligent multi-objective optimization strategy for high strength sheet metal forming process was suggested based on genetic algorithm. Latin Hypercube Sampling method was introduced to design the rational experimental samples; the objective function was defined based on crack factor, wrinkle factor and severe thinning factor; the accurate response surface model for sheet metal forming problem was built; Multi-objective genetic algorithm was adopted in optimization and Pareto solution was selected. The strategy was applied to analyze a rocher. The result has proved this strategy suitable for optimization design of sheet metal forming process .

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