MULTI-RESPONSE OPTIMIZATION OF DIELECTRIC FLUID MIXTURE IN EDM USING GREY RELATIONAL ANALYSIS (GRA) IN TAGUCHI METHOD
In the current study, combining the powder with dielectric fluid in electrical discharge machining (PMEDM) is a very fascinating technological approach. This approach is the most effective at increasing both productivity and the quality of a machined surface at the same time. The Taguchi–GRA approach was used to optimize the surface roughness (SR), material removal rate (MRR), and micro-hardness of a machined surface (HV) in electrical discharge machining of die steels in dielectric fluid with mixed powder. Workpiece materials (with 3 levels such as SKD61, SKD11, and SKT4), electrode materials (with 2 levels such as copper, and graphite), pulse-on time, electrode polarity, current, pulse-off time, and titanium powder concentration were all used in the study. The effect on the ideal results was also evaluated using some interaction pairings among the process parameters. Powder concentration, electrode material, electrode polarity, current, pulse-on time, pulse-off time, and Interaction between workpiece material and powder concentration were obtained to be significant in the ideal condition, where larger MRR and HV are wanted (as per the HB criterion), but lower values are desired for the remaining responses, such as surface roughness (SR). Powder concentration was also discovered to be a major component, however, it only accounts for 8.35 percent of the ideal condition. MRR = 54.36 mm3/min, SR = 5.65 m, and HV =832.66 HV were the best quality attributes based on the grey grade.
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