Electro jet drilling using hybrid NNGA approach

Authors:
Mohan Sen;H. S. Shan
Affiliations:
Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247 667, India;Mechanical and Industrial Engineering Department, Indian Institute of Technology Roorkee, Roorkee 247 667, India
Venue:
Robotics and Computer-Integrated Manufacturing
Year:
2007

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Abstract

This paper presents a hybrid neural network and genetic algorithm (NNGA) approach for the multi-response optimization of the electro jet drilling (EJD) process. The approach first uses a neural network model to predict the response parameters of the process. A genetic algorithm is then applied to the trained neural network model to obtain the optimal process parameters values in which desirability function approach is used to obtain the fitness function for the genetic algorithm from the network output. The simulated results are found to have a close correlation with the experimental data.