This work presents a study on multi-objective optimization of the powder-mixed electrical discharge machining (PMEDM) method for cutting cylindrical parts made of 90CrSi tool steel. The study focused on three specific objectives: achieving the lowest possible surface roughness (SR), minimizing electrode wear rate (EWR), and maximizing material removal rate (MRR). Furthermore, a variety of input parameters have been chosen for the experiment, such as the powder concentration Cp, the pulse-on time Ton, the pulse-off time Toff, the pulse current IP, and the servo voltage SV. Furthermore, the experiment involved the utilization of graphite electrodes and the incorporation of SiC powder into the Diel MS 7000 dielectric solution. In addition, the Taguchi and grey relation analysis (GRA) methodologies were employed for experiment design and outcome analysis. An assessment was conducted to determine the impact of the input elements on the multi-criteria target. In addition, the necessary input parameters to achieve the aforesaid single objective functions simultaneously were provided.

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A Study on Multi-objective Optimization of PMEDM 90CrSi Tool Steel Using Graphite Electrodes

  • Phan Dang Phong,
  • Vu Ngoc Pi,
  • Hoang Xuan Tu,
  • Dinh Van Thanh,
  • Nguyen Van Tung

摘要

This work presents a study on multi-objective optimization of the powder-mixed electrical discharge machining (PMEDM) method for cutting cylindrical parts made of 90CrSi tool steel. The study focused on three specific objectives: achieving the lowest possible surface roughness (SR), minimizing electrode wear rate (EWR), and maximizing material removal rate (MRR). Furthermore, a variety of input parameters have been chosen for the experiment, such as the powder concentration Cp, the pulse-on time Ton, the pulse-off time Toff, the pulse current IP, and the servo voltage SV. Furthermore, the experiment involved the utilization of graphite electrodes and the incorporation of SiC powder into the Diel MS 7000 dielectric solution. In addition, the Taguchi and grey relation analysis (GRA) methodologies were employed for experiment design and outcome analysis. An assessment was conducted to determine the impact of the input elements on the multi-criteria target. In addition, the necessary input parameters to achieve the aforesaid single objective functions simultaneously were provided.