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<p>Near-dry electric discharge machining (ND-EDM) is an advanced machining technique designed for the precision processing of hard-to-machine materials. This method employs controlled electrical discharges to generate localized heat, facilitating the removal of material with minimal thermal damage. ND-EDM offers notable advantages in terms of performance efficiency and surface integrity. The present study aims to optimize key performance parameters of the ND-EDM process, specifically focusing on material removal rate (MRR) and surface roughness (SR). EN-31 steel was selected as the workpiece material due to its industrial relevance and challenging machinability. To achieve multi-response optimization, an objective weighting approach incorporating standard deviation was adopted in conjunction with multi-attribute decision-making (MADM) technique. The experimental investigation analyzed the effects of four process parameters – discharge current, voltage, pulse duration (pulse on-time), and mist pressure. A Taguchi-based grey relational analysis (GRA) was performed in Minitab 19 software, using an L27 orthogonal array with 27 experimental trials. Analysis of variance (ANOVA) was conducted to determine the statistical significance of the input parameters on MRR and SR. Based on the optimization results, the parameter combination <i>A1B1C1D2</i> was identified as the optimal configuration for achieving superior machining performance in ND-EDM.</p>

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Experimental investigation of ND-EDM and traditional EDM process parameters using multi-attribute decision-making optimization

  • 期刊论文

  • 发表日期：

    2026年4月13日

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  • Ajit,
  • Sanjay Sundriyal,
  • Nitish Kaushik

摘要

Near-dry electric discharge machining (ND-EDM) is an advanced machining technique designed for the precision processing of hard-to-machine materials. This method employs controlled electrical discharges to generate localized heat, facilitating the removal of material with minimal thermal damage. ND-EDM offers notable advantages in terms of performance efficiency and surface integrity. The present study aims to optimize key performance parameters of the ND-EDM process, specifically focusing on material removal rate (MRR) and surface roughness (SR). EN-31 steel was selected as the workpiece material due to its industrial relevance and challenging machinability. To achieve multi-response optimization, an objective weighting approach incorporating standard deviation was adopted in conjunction with multi-attribute decision-making (MADM) technique. The experimental investigation analyzed the effects of four process parameters – discharge current, voltage, pulse duration (pulse on-time), and mist pressure. A Taguchi-based grey relational analysis (GRA) was performed in Minitab 19 software, using an L27 orthogonal array with 27 experimental trials. Analysis of variance (ANOVA) was conducted to determine the statistical significance of the input parameters on MRR and SR. Based on the optimization results, the parameter combination A1B1C1D2 was identified as the optimal configuration for achieving superior machining performance in ND-EDM.