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Modeling of Material Removal Rate in Micro EDM Using Neural Network
Abstract
In micro-electrical discharge machining (Micro EDM) machining, material removal rate (MRR) is the particular main output parameter. Here we will discover various machining parameters get an effect on the particular MRR. For production industries, to maximize the results from Micro EDM, appropriate predictive designs for MRR must end up being constructed. This particular report utilizes neural network modeling to predict MRR over the particular machining time for assortment of cutting conditions around EDM. Some experimental data for machining of mild steel are obtained along with the experimental data obtained via conducted findings on EDM in the particular lab. The data-sets from MRR were utilized to learn the particular neural network models. Trained neural network models were utilized in predicting MRR to get other cutting conditions.
Keywords: advanced machining methods, advanced manufacturing methods, EDM, MRR, MLP, neural network, optimization, RBF
Keywords: advanced machining methods, advanced manufacturing methods, EDM, MRR, MLP, neural network, optimization, RBF
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PDFDOI: https://doi.org/10.37628/ijmdic.v4i1.714
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