Optimization of machining parameters in wire electrical discharge machine process by combination of genetic algorithm and artificial neural network
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 2
Abstract
Wire electrical discharge machining (WEDM) has become an important non-traditional machining process. Wire Electrical discharge machining (WEDM) process, at present is still an experience process, wherein selected parameters are often far from the optimum, and at the same time selecting optimization parameters is costly and time consuming. In this paper, artificial neural network (ANN) and genetic algorithm (GA) are used together to establish the parameter optimization model. An ANN model which adapts Levenberg-Marquardt algorithm has been set up to represent the relationship between material removal rate (MRR) and input parameters, and GA is used to optimize parameters, so that optimization results are obtained. The model is shown to be effective, the main objective is to select proper machining parameters to get high Material Removal Rate (MRR).
Authors and Affiliations
Rajesh S, Nandhakumar S
Keywords
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