Powder mixed electrical discharge machining (PMEDM) is a new machining technology. The optimization of process parameters in PMEDM is being researched. The determination of the value of the weights of quality indicators in a multiobjective optimization problem is often complex and difficulty. Preferential selection index (PSI) is a new computational technique for solving multi-objective problems. This contributes to the process of solving the multi-objective optimization problems. In this study, material removal rate (MRR) and surface roughness (SR) were optimized with the help of the PSI method. The specimen and tool materials, electrode polarity, current, pulse-on-time, pulse-off-time and powder concentration were considered. The investigation showed that powder concentration can increase MRR with lower SR. The most significant factor was the electrode material. The optimal values were found as SKD11 (workpiece), Gr (tool), + (polarity), 5 ㎲ (ton), 57 ㎛ (toff), 8A (current) and 10 g/l (powder concentration) with a high accuracy of 7.82%. The electrode material and powder concentration could provide strong influence on the performance measures owing to their importance on determining spark energy in the PMEDM. The research results were compared with those of TOPSIS, GRA and MOORA methods. In conclusion, PSI is the method for the highest efficiency.
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