Optimization of Multi-Performance Parameters in EDM through Grey Relational Analysis using Deionized Water

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Authors

  • Devesh Pratap Singh
     Centre for Advanced Studies, Lucknow – 226031, Uttar Pradesh ,IN
  • Sharad Yadav
     Centre for Advanced Studies, Lucknow – 226031, Uttar Pradesh ,IN
  • Naman Sisodia
     Centre for Advanced Studies, Lucknow – 226031, Uttar Pradesh ,IN
  • Dipesh Kumar Mishra
     Centre for Advanced Studies, Lucknow – 226031, Uttar Pradesh ,IN
  • Rabesh Kumar Singh
     Centre for Advanced Studies, Lucknow – 226031, Uttar Pradesh ,IN

DOI:

https://doi.org/10.18311/jmmf/2023/45492

Keywords:

EDM, GRA, MRR, Optimization, Surface Roughness

Abstract

This study includes an experimental study of the effect of input process parameters on output parameters during the EDM of C-20 mild steel. Deionized water is being investigated as a sustainable alternative to Electrical Discharge Machining (EDM) oil, reducing toxic emissions and enhancing process sustainability. ANOVA results revealed that current and voltage had the largest impact on MRR, while TON significantly affected TWR and TON had the greatest influence on surface roughness. The study found that increasing the current and voltage resulted in significant increases in MRR (164.78% and 99.49%, respectively) and TWR (21.19% and 26.02%, respectively). However, an improve in TON led to a decrease in TWR (by 66.7%) but an increase in MRR (by 59.57%). Increased current, voltage, and TON result in a 74.34%, 72.14%, and 108.15% improvement in surface roughness, respectively. The Grey relational analyses were used for best optimum result which comes on parameters current 12 amps, voltage 20 volts and TON 200 μs.

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Published

2024-09-05

How to Cite

Singh, D. P., Yadav, S., Sisodia, N., Mishra, D. K., & Singh, R. K. (2024). Optimization of Multi-Performance Parameters in EDM through Grey Relational Analysis using Deionized Water. Journal of Mines, Metals and Fuels, 71(12B), 12–20. https://doi.org/10.18311/jmmf/2023/45492

Issue

Volume 71, Issue 12B , 2023

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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