Springback Predictions for Sheet Metal Forming using the Finite Element Method with Data Mining Techniques

This paper presents a new method to predict the springback in sheet metal forming. First the genetic algorithm (GA) is adopted for recognizing the material parameters. According to the even design idea, the calculation scheme is selected and the finite element method (ANSYS/LS-DYNA 5.71) is used for calculating the springback. Compared with the calculations and experiments, the difference between the two results is taken as source data, a new pattern recognition method of data mining called hierarchical optimal map recognition (HOMR) method is applied for summarizing the calculation regulation in finite element method. In the end, the mathematics model of the springback simulation has been established. Based on the model, the calculation error of springback can be controlled within 10% compared with the experiments.

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