With the combination of the
mathematical theory of plasticity, orthogonal test and the technology of
artificial neural network,
an intelligent prediction system was established to calculate the drawing load of cup drawing precisely. According to Hill's anisotropic theory, a new theoretical formula was derived to compute the drawing load variations and the maximum drawing load. The technological parameters affecting the maximum drawing load were analyzed by applying orthogonal tests and the following conclusions are drawn: 1) At the notability level of one percent, the maximum drawing load is relevant to blank holder pressure, the radius of the die arc, and the type of lubricant; 2) The most notable factor affecting the maximum drawing load is the type of lubricant, the second is the radius of the die arc, then the blank holder pressure and the radius of the punch arc. By applying the
artificial neural network, the theoretical formula and the experimental data were combined so that the model error of the theoretical formula was mended, which enhances the accuracy of prediction. Two key problems encountered in the application of BP network were discussed and the solutions were given. Then the intelligent prediction system was constructed, which is not only practically applicable in engineering, but also valuable for the better understanding of the cup drawing behavior of sheet metal. <