Using EAMR Method to Find Best Input Parameters for PMEDM SKD11 Tool Steel

The paper shows the findings of a study that utilized Multi-Criteria Decision-Making (MCDM) to determine the best input parameters for machining cylindrical parts made of SKD11 tool steel using Powder-Mixed Electrical Discharge Machining (PMEDM). The experiment consisted of six input elements: Powder concentration (Cp), powder size (Sp), pulse on time (Ton), pulse off time (Toff), pulse current (IP), and servo voltage (SV). Moreover, the Taguchi methodology was utilized for the experimental design. The EAMR methodology was utilized to address the MCDM problem, employing the Entropy method for estimating the criteria weights. The objective was to achieve a high rate of material removal speed (MRS) while limiting the rate of electrode wear (EWR). The solution for the MCDM problem in the PMEDM of cylindrically shaped components was found based on the discovered results.