Milan Kumar Das

Optimization of Material Removal Rate in EDM Using Taguchi Method

This paper presents an investigation on the effect and optimization of machining parameters on material removal rate (MRR) in electrical discharge machining (EDM) of EN31 tool steel. For the experiment, four process parameters viz. pulse on time, pulse off time, discharge current and voltage are considered. The settings of machining parameters are determined by using Taguchis orthogonal array (OA). L27 orthogonal array (OA) is considered for the study. The level of importance of the machining parameters on MRR is determined by analysis of variance (ANOVA) test. The optimum machining parameter combination is obtained by the analysis of signal-to-noise (S/N) ratio. The analysis shows that discharge current has the most significant effect on MRR followed by pulse off time and voltage. It is seen that with an increase in discharge current and pulse off time, MRR increases in the studied range. The methodology described here is expected to be highly beneficial to manufacturing industries.

Optimisation of EDM process parameters using grey-Taguchi technique

This paper presents an experimental study of material removal rate (MRR) and roughness characteristics in electrical discharge machining (EDM) of EN 31 tool steel. Experiments are carried out by utilising the combination of four process parameters viz. pulse on time, pulse off time, discharge current and voltage based on L27 Taguchi orthogonal array. Multi-response optimisation of EDM process parameters is done with respect to MRR and five different surface roughness characteristics based on Taguchi method coupled with grey relational analysis. Analysis of variance (ANOVA) is performed and it is observed that current is the significant process parameter that affects the responses. Optimal setting has been verified through confirmation test and the result shows a good agreement with the predicted value. This indicates utility of the grey-Taguchi technique as a multi-objective optimiser in the field of EDM. Also, the surface morphology is studied with the help of scanning electron microscopy.

Effect of Process Parameters on MRR and Surface Roughness in ECM of EN 31 Tool Steel Using WPCA

WeightedprincipalcomponentanalysisisusedtopredicttheoptimalmachiningparametersforEN 31toolsteelinelectrochemicalmachiningforminimumsurfaceroughnessandmaximummaterial removalratebasedonL27Taguchiorthogonaldesign.Forthis,multi-responseperformanceindexis calculatedtoderiveanequivalentsingleobjectivefunctionandthenTaguchimethodisusedtooptimize theprocessparameters.Theseparableinfluenceofindividualmachiningparametersandtheinteraction between theseparameters arealso investigatedbyusinganalysisofvariance (ANOVA).Results showthatthemainsignificantfactoronMRRandsurfaceroughnessiselectrolyteconcentration. Theeffectsofprocessparametersviz.electrolyteconcentration,voltage,feedrateandinter-electrode gaponMRRandsurfaceroughnessarealsoinvestigatedusing3Dsurfaceandcontourplots.Finally, thesurfacemorphologyisstudiedwiththehelpofscanningelectronmicroscopy(SEM)images. KEyWoRdS ECM, MRR, Optimization, Surface Roughness, WPCA