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Objectives: Electro discharge machining (EDM) has been widely and effectively utilized as one of the niche cost-effective technology for machining of extremely tough, brittle and unique metals and alloys. However, obtaining a larger material removal rate (MRR) as well as diminished tool wear rate (TWR) with improved surface finish and minimum amount of overcut is the major challenging issue in the research field of EDM. This paper puts light on the aforesaid aspects of EDM through optimization techniques using Taguchi and Grey Relational Analysis. Methods/Statistical Analysis: The work piece material selected is circular shaped EN19 alloy steel and the tool is rectangular shaped Copper. Taguchi parametric design with L27 orthogonal array is utilized to conduct 27 experiments. With an objective to optimize the machining performance variables such as material removal rate (MRR), tool wear rate (TWR), machined surface roughness (SR) as well as the overcut (OC), a number of operational parameters of the machining process such as Pulse on time (Ton), open circuit current (Ip) and pulse duty factor (Tau) are consciously chosen. A statistical technique, Analysis of variance (ANOVA), is pursued to determine the pertinent parameters swaying the responses. Finally, the contours of machining characteristics are drawn to get a clear visualization of the effect of the crucial input variables on the process performances. Findings: As an outcome of the research, pulse on time was observed to be a relatively more influential parameter swaying MRR and TWR followed by open circuit current and then pulse duty factor. Further, the work is extended by performing Grey Relational Analysis (GRA) to get a suitable combination of critical parameters in order to optimize the overall machining performance of EDM. The suitable combination of input parameters are IP = 30 A, Ton = 3000 μs, Tau = 12 resulting maximum MRR, minimum TWR, minimum SR, and minimum OC. Application/Improvements: Very less paper are reported on optimization of all the crucial machining responses such as MRR, SR, TWR and OC simultaneously using a rectangular shaped tool. However, this paper results an appropriate combination of machining parameters in order to optimize all the aforesaid responses together taking the complexity of tool as well.

Keywords

ANOVA, EDM, GRA, MRR, OC, SR, TWR.
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