Optimization of Surface Roughness and MRR in Electrochemical Machining of EN31 Tool Steel Using Grey-taguchi Approach

Electrochemical machining is one of the widely used non-traditional machining processes to machine complicated shapes for electrically conducting but difficult-to-machine materials such as super alloys, Ti-alloys, alloy steel, tool steel, stainless steel, etc. Use of optimal ECM process parameters can significantly reduce the ECM operating, tooling, and maintenance cost and will produce components with higher accuracy. This paper investigates the effect of process parameters on material removal rate (MRR) and surface roughness characteristic (centre line average roughness: Ra, root mean square roughness: Rq, skewness: Rsk, kurtosis: Rku and mean line peak spacing: Rsm) and parametric optimization of process parameters in ECM of EN31 tool steel using grey relation analysis. Experiments are conducted based on Taguchi's L27 orthogonal array (OA) with four process parameters viz. electrolyte concentration, voltage, feed rate and inter-electrode gap. Analysis of variance (ANOVA) is performed to get the contribution of each parameter on the performance characteristics and it is observed that electrolyte concentration is the significant process parameter that affects the responses. The experimental results for the optimal setting show that there is considerable improvement about 48% in the process using confirmation test. The optimal combination is electrolyte concentration 10%, voltage 10 V, feed rate 0.25 mm/min and inter-electrode gap 0.2 mm for maximum MRR and minimum surface roughness. Surface and contour plots are generated to study the effect of input parameters on MRR and surface roughness. Finally, scanning electron microscopy (SEM) images are used to observe the surface morphology.