Abstract
Herein, an experimental investigation has been conducted to determine the machining quality of AISI 202 grade stainless steel by copper alloy electrode Cu-Cr-Zr facilitated on electro discharge machining (EDM). Furthermore, the impact of controllable parameters: pulse current, pulse off time, and pulse on time were investigated to show the relationship with material removal rate and electrode wear rate, respectively. The optimum parameters are obtained by incorporating response surface methodology and the significant effects of paramount controllable parameters computed by a statistical methodology analysis of variance. The surface produced by EDM was investigated through a scanning electron microscope, respectively. The presence of micro-cracks and recast layer urge reduction of thermal stress generated during machining and attendance of globules and white layer protected the electrode from thermal erosion significantly. Finally, the machining behavior was embossed with an artificial neural network (ANN) having a feed-forward back propagation neural network with two layers and 20 neurons. The results depict close agreement of predicted value with experimental results.
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