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To run any machine effectively and economically, the effect of different process variables on the performance must be known. An experimental investigation is costly, time-consuming as well as difficult for a complete understanding of the EDM process. Hence, several researchers have developed various models of the process using different approaches like mathematical modeling, finite element analysis, regression modeling, dimensional analysis, etc. based on certain assumptions and simplifications, which limit the accuracy of prediction. In this article, a novel modeling approach is presented to predict material removal rate (MRR) and tool wear rate (TWR) during machining of AISI D2 tool steel by the copper electrode using the full factorial design. The validation was carried out using Taguchi’s L9 orthogonal array-based confirmation experiments. The results showed that these models can be used for prediction of MRR and TWR at any set of process parameters for a given combination of workpiece and tool with good accuracy.

Modelling of material removal rate and tool wear rate in EDM based on a fraction of energy approach