To achieve better precision of features generated using the micro-electrical dischargemachining (micro-EDM), there is a necessity to minimize the wear of the toolelectrode, because a change in the dimensions of the electrode is reflected directly orindirectly on the feature. This paper presents a novel modeling and analysis approachof the tool wear in micro-EDM using a systematic statistical method exemplifying theinfluences of capacitance, feed rate and voltage on the tool wear ratio. The associationbetween tool wear ratio and the input factors is comprehended by using main effectplots, interaction effects and regression analysis. A maximum variation of four-fold inthe tool wear ratio have been observed which indicated that the tool wear ratio variessignificantly over the trials. As the capacitance increases from 1 to 10 nF, the increasein tool wear ratio is by 33%. An increase in voltage as well as capacitance would leadto an increase in the number of charged particles, the number of collisions amongthem, which further enhances the transfer of the proportion of heat energy to the toolsurface. Furthermore, to model the tool wear phenomenon, a regression relationshipbetween tool wear ratio and the process inputs has been developed.
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