Neural network modelling and parameters optimization of increased explosive electrical discharge grinding (IEEDG) process for large area polycrystalline diamond

This paper addresses a neural network (NN) model for the increased explosive electrical discharge grinding (IEEDG) process. A genetic algorithm (GA) was then applied to the trained neural network model to determine the optimal process parameter values, in which grey relational analysis (GRA) is conducted to determine the weights of the two performance characteristics. The integrated NN–GRA–GA system was successful in determining the optimal process parameter when obtaining the overall better performance is considered. The results of verification experiments have shown that machining performance in the IEEDG process can be improved effectively through this approach.