Prediction of life of deep drawing die using artificial neural network

Abstract

In this paper, research work involved in the prediction of life of deep drawing die using artificial neural network (ANN) is described. The parameters affecting life of deep drawing die such as size and material of die block and punches are investigated through finite element (FE) analysis and the critical simulation values are determined. Based on FE analysis results, stress amplitude (S) vs. cycles to failure (N) approach is used for prediction of number of cycles of deep drawing die. The number of cycles gives the number of sheet metal parts that can be produced with the deep drawing die before its failure. The ANN model of the proposed system is developed using MATLAB. The data required for ANN are obtained from FE analysis. The generated output data from FE analysis are used to train ANN model. The developed ANN model predicts the life of deep drawing die in terms of number of sheet metal parts. Usefulness of the proposed system is demonstrated through an example of an industrial sheet metal part.

Keywords:

• Artificial neural network (ANN)
• deep drawing die
• MATLAB
• sheet metal