Application of grey-fuzzy logic for the optimization of process parameters on CNC turning of EN8-steel

Abstract

This paper presents an effective approach of greyfuzzy logic to optimize the cutting parameters in CNC turning with respect to multiple roughness characteristics. Four cutting parameters, namely, depth of cut, spindle speed, feed rate and nose radius are optimized considering three surface roughness parameters; centre line average, peak-valley height and maximum height of profile. An orthogonal array (L27), grey relational generation, grey relational coefficient and grey –fuzzy grade obtained from the grey relational analysis which is used as performance index to solve the optimization problem of turning parameters for EN-8 steel. Taguchi orthogonal array, the signal-to-noise ratio, and the analysis of variance are used to investigate the optimal levels of cutting parameters. The confirmation tests are conducted to verify the results and it is observed that grey-fuzzy approach is efficient in determining the optimal cutting parameters based on multiple surface roughness characteristics.