Optimization of Process Parameters in Plasma arc Cutting of EN 31 Steel Based on MRR and Multiple Roughness Characteristics Using Grey Relational Analysis

Abstract

This paper investigates the effects and parametric optimization of process parameters for plasma arc cutting (PAC) of EN31 steel using grey relation analysis. Three process parameters viz. gas pressure, arc current and torch height are considered and experiments are conducted based on L27 orthogonal array (OA). Process responses viz. material removal rate (MRR) and surface roughness parameters (centre line average roughness: Ra, root mean square: Rq, skewness: Rsk, kurtosis: Rsk and mean line peak spacing: Rsm) of the machined surface are measured for every experimental runs. For maximum MRR and minimum surface roughness characteristics process parameters are optimized based on Taguchi method coupled with grey relational analysis. Analysis of variance (ANOVA) is performed to get the contribution of each process parameters on the performance characteristics and it is observed that gas pressure is significant process parameter that affects the responses. Confirmation test using optimal setting shows good agreement to the predicted value. This indicates utility of the grey-Taguchi technique as a multi-objective optimizer in the field of PAC. Finally, using scanning electron microscopy, the surface morphology is studied.