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2026 Singh SK2MCr4 EDM Parameter Modeling

Yogesh Kumar Singla, Deepa Singh

2026enelectrical discharge machininghardened steelmaterial removal rateprocess optimizationTaguchi methodregression modeling

Abstract

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This study investigates the impact of key electrical discharge machining (EDM) parameters: specifically, current, pulse on time, and servo voltage on the material removal rate (MRR) for SK2MCr4 steel. A comprehensive experimental approach employing a full factorial design was utilized to explore both the individual and interaction effects of these parameters. To enhance efficiency and precision, the Taguchi method, in conjunction with ANOVA, was applied for process optimization. The findings revealed that electric current is the most significant factor, accounting for approximately 64–73% of the variance in MRR, followed by pulse on time and servo voltage. The optimal parameters identified include a current of 12 A, a pulse on time of 60 µs, and a servo voltage of 3 V, which resulted in the highest MRR and robust process performance. The regression models demonstrated substantial predictability with R² values exceeding 89%, thereby affirming the importance of the selected factors. Interaction analysis highlighted synergistic effects between current and pulse on time, emphasizing the necessity of multi-variable optimization.

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Cite This Work

@article{1364c44e-e6f9-4c4c-8ac1-77121a91d1ae,
  title={2026 Singh SK2MCr4 EDM Parameter Modeling},
  author={Yogesh Kumar Singla and Deepa Singh},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - 2026 Singh SK2MCr4 EDM Parameter Modeling
AU  - Yogesh Kumar Singla
AU  - Deepa Singh
PY  - 2026
LA  - en
ER  -

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