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This paper presents the findings of a study that utilized Multi-Criteria Decision-Making (MCDM) to identify the most suitable input parameters for manufacturing cylindrical components using Powder-Mixed Electrical Discharge Machining (PMEDM) with SKD11 tool steel. This experiment utilized six input components: powder concentration Cp, powder size Sp, pulse on time Ton, pulse off time Toff, pulse current IP, and servo voltage SV. In addition, the Taguchi technique was adopted for the experimental design. The MAIRCA methodology was implemented to handle the MCDM problem, employing the Entropy method for estimating criterion weights. The objective was to achieve a high material removal speed (MRS) and a low electrode wear rate (EWR). The solution for the MCDM problem in PMEDM cylindrically shaped parts was found based on the findings.

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Application of MAIRCA Technique to Find Best Input Factors When PMEDM SKD11 Tool Steel

  • 会议论文

  • 发表日期：

    2025年

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  • Le Duc Bao,
  • Nguyen Van Trang,
  • Vu Duc Binh,
  • Muthumaralingam Thangaraj,
  • Hoang Xuan Tu

摘要

This paper presents the findings of a study that utilized Multi-Criteria Decision-Making (MCDM) to identify the most suitable input parameters for manufacturing cylindrical components using Powder-Mixed Electrical Discharge Machining (PMEDM) with SKD11 tool steel. This experiment utilized six input components: powder concentration Cp, powder size Sp, pulse on time Ton, pulse off time Toff, pulse current IP, and servo voltage SV. In addition, the Taguchi technique was adopted for the experimental design. The MAIRCA methodology was implemented to handle the MCDM problem, employing the Entropy method for estimating criterion weights. The objective was to achieve a high material removal speed (MRS) and a low electrode wear rate (EWR). The solution for the MCDM problem in PMEDM cylindrically shaped parts was found based on the findings.