Application of artificial neural network and Taguchi method to preform design in metal forming considering workability

摘要

This study describes a new method of perform design in muti-stage metal forming processes considering workability limited by ductile fracture. The finite element simulation combined with ductile fracture criterion has been performed in order topredict ductile fracture. The artificial neural network using the Taguchi method has been implemented for minimizing objective functions relevant to the forming process. The combinations of design parameters used in finite element simulation are selectedby orthogonal array in statistical design of experiments. The orthogonal array and the result of simulation are used as train data for artificial neural networks. The cold heading process is taken as an example of designing preforms which do not form anyfracture in the finished product. The results of analysis to validate the proposed design method are presented.