A Comparative Investigation on Powder Mixed EDM Machining of Steel Alloys with Multi-Objective Optimization Using Fuzzy-TOPSIS Method

The current work offers a comparative study that examined the effects of various process parameters, such as dielectric fluid, current (IP), pulse on time (TON), and different conductive powder particles mixed dielectric fluids, on electrical discharge machining (EDM) of AISI 1040, EN31, and HCHCr steels, respectively. The findings indicate that adding conductive particles to the dielectric medium during the powder-mixed EDM (PMEDM) process enhances energy distribution across the spark gap, thereby improving material removal capacity and the surface characteristics of the machined surfaces. Experimental results show that the concentration of powder particles has the most significant impact on surface roughness (Ra) and tool wear rate (TWR), while the most critical factor affecting the material removal rate (MRR) is the current (IP). Additionally, increasing the IP and TON leads to the formation of continuous, thick cracks and a thin white coating on the EDMed surface, as evidenced by scanning electron microscopy (SEM) images of the surface morphology. The study also employs a multi-optimization technique using the Fuzzy-based TOPSIS method to investigate the cumulative effects of the control parameters on performance indicators, namely Ra, MRR, and TWR. In experimental run 8 i.e. moderate IP (5 A), higher TON (180 µs), and higher concentration of copper powder (10 g/l) mixed in EDM oil while machining of AISI 1040, the optimal results i.e. Ra is 5.983 µm, MRR is 27.243 mm3/min, and TWR is 0.775 mm3/min were obtained, respectively.

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Publication Details

Journal
Diyala Journal of Engineering Sciences
Published
2024-12-01
DOI
https://doi.org/10.24237/djes.2024.17402
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
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article

A Comparative Investigation on Powder Mixed EDM Machining of Steel Alloys with Multi-Objective Optimization Using Fuzzy-TOPSIS Method

Naveen Kumar, Mohd Atif Wahid, Md Nadeem Alam, Salaheddin Sabri et al.
Diyala Journal of Engineering Sciences
Advanced Machining and Optimization Techniques
article

A Comparative Investigation on Powder Mixed EDM Machining of Steel Alloys with Multi-Objective Optimization Using Fuzzy-TOPSIS Method

Naveen Kumar, Mohd Atif Wahid, Md Nadeem Alam, Salaheddin Sabri, Raghib Ahsan
article en

Abstract

The current work offers a comparative study that examined the effects of various process parameters, such as dielectric fluid, current (IP), pulse on time (TON), and different conductive powder particles mixed dielectric fluids, on electrical discharge machining (EDM) of AISI 1040, EN31, and HCHCr steels, respectively. The findings indicate that adding conductive particles to the dielectric medium during the powder-mixed EDM (PMEDM) process enhances energy distribution across the spark gap, thereby improving material removal capacity and the surface characteristics of the machined surfaces. Experimental results show that the concentration of powder particles has the most significant impact on surface roughness (Ra) and tool wear rate (TWR), while the most critical factor affecting the material removal rate (MRR) is the current (IP). Additionally, increasing the IP and TON leads to the formation of continuous, thick cracks and a thin white coating on the EDMed surface, as evidenced by scanning electron microscopy (SEM) images of the surface morphology. The study also employs a multi-optimization technique using the Fuzzy-based TOPSIS method to investigate the cumulative effects of the control parameters on performance indicators, namely Ra, MRR, and TWR. In experimental run 8 i.e. moderate IP (5 A), higher TON (180 µs), and higher concentration of copper powder (10 g/l) mixed in EDM oil while machining of AISI 1040, the optimal results i.e. Ra is 5.983 µm, MRR is 27.243 mm3/min, and TWR is 0.775 mm3/min were obtained, respectively.

Diyala Journal of Engineering Sciences
Dr. A.P.J. Abdul Kalam Technical University (IN), Jamia Millia Islamia (IN), Sharda University (IN)
Affordable and clean energy
Openalex Percentile: Top 80%
Advanced Machining and Optimization Techniques
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