Affiliation:
1. S. V. National Institute of Technology
2. Sardar Vallabhbhai National Institute of Technology
Abstract
Prediction of life of compound die is an important activity usually carried out by highly experienced die designers in sheet metal industries. In this paper, research work involved in the prediction of life of compound die using artificial neural network (ANN) is presented. The parameters affecting life of compound die are investigated through FEM analysis and the critical simulation values are determined. Thereafter, an ANN model is developed using MATLAB. This ANN model is trained from FEM simulation results. The proposed ANN model is tested successfully on different compound dies designed for manufacturing sheet metal parts. A sample run of the proposed ANN model is also demonstrated in this paper.
Publisher
Trans Tech Publications, Ltd.
Subject
Mechanical Engineering,Mechanics of Materials,General Materials Science
Reference19 articles.
1. E. Ostergaard, Advanced Diemaking, (McGraw-Hill. Inc. USA, 1967).
2. A. Forcellese, F. Gabrielli and R. Ruffini, Effect of the training set size on springback control by neural network in an air bending process, Journal of Materials Processing Technology, Vol. 80–81 (1998), p.493–500.
3. R. Roy, Assessment of Sheet-Metal Bending Requirements Using Neural Networks, Neural Computing & Applications, Vol. 4 (1996), pp.35-43.
4. Z. C. Lin and H. Chang, Application of fuzzy set theory and back propagation neural networks in progressive die design, Journal of manufacturing system, Vol. 15 (4) (1996), pp.268-281.
5. R. Hambli, Optimization of Blanking Processes Using Neural Network Simulation, The Arabian Journal for Science and Engineering, Vol. 30 (2005), pp.3-16.
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