Determination of Best Input Factors in Powder-Mixed Electrical Discharge Machining 90CrSi Steel using Multi-Criteria Decision Making Methods
Received: 3 October 2024 | Revised: 28 October 2024 | Accepted: 16 November 2024 | Online: 2 February 2025
Corresponding author: Van Tung Nguyen
Abstract
This article outlines the results of a Multi-Criteria Decision Making (MCDM) analysis conducted on the Powder-Mixed Electrical Discharge Machining (PMEDM) process for cylindrical parts fabricated from 90CrSi tool steel, using graphite electrodes. The study aims to identify the optimal input factors to simultaneously minimize Surface Roughness (SR) and Electrode Wear Rate (EWR), while maximizing Material Removal Speed (MRS). Five input factors were selected: powder concentration (CP), pulse-on time (Ton), pulse-off time (Toff), pulse current (IP), and servo voltage (SV). Experimental data were generated using the Taguchi method with an L18 design. The optimization process was performed using the Multi-Attributive Border Approximation area Comparison (MABAC), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Evaluation by an Area-based Method of Ranking (EAMR) methods. Criteria weights were calculated utilizing the Entropy and the Multi-Expert Ranking Evaluation with Compensation (MEREC) techniques. The analysis identified the best PMEDM input factor, providing an optimal solution for enhancing the efficiency of machining cylindrically shaped components.
Keywords:
PMEDM, MCDM, MABAC, TOPSIS, EAMR, surface roughness, electrode wear rate, material removal rate, 90CrSi tool steel, graphite electrodesDownloads
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Copyright (c) 2024 Van Tung Nguyen, Van Thanh Dinh, Dang Phong Phan, Duc Binh Vu, Ngoc Pi Vu

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