Investigating electrochemical drilling (ECD) using statistical and soft computing techniques

In the present study, five modeling approaches of RA, MLP, MNN, GFF, and CANFIS were applied so as to estimate the radial overcut values in electrochemical drilling process. For these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. The developed models were evaluated in terms of their prediction capability with measured values. It was clearly seen that the proposed models were capable of predicting the radial overcut. However, the MLP model predicted the radial overcut with higher accuracy than the other models. The statistical analysis showed how much the radial overcut was mainly influenced by voltage and electrolyte concentration during the electrochemical drilling process.

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