Artificial Neural Network Modeling and Optimization using Genetic Algorithm of Machining Process
Pragya ShandilyaAbhishek Tiwari
Abstract
In the present work an attempt is made to model and optimize the complex wire electric discharge machining (WEDM) using soft computing techniques. The purpose of this research work is to develop the artificial neural network (ANN) model to predict the cutting width (kerf) during WEDM. Genetic algorithm (GA) was used to optimize the process parameters. Experiments were carried out over a wide range of machining condition for training and verification of the model. In this work four input parameters namely servo voltage, pulse-on time, pulse-off time and wire feed rate were used to develop the ANN model. Training of the neural network model was performed on 29 experimental data points.
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