Multi-response optimisation during face milling of polyoxymethylene copolymer using grey relational analysis and data envelopment analysis based ranking coupled with the Taguchi approach

Abstract

ABSTRACT The present work aims to evaluate the effect of cutting factors, namely cutting speed (Vc), feed per tooth (fz), and depth of cut (ap) on surface quality (average arithmetic roughness Ra and total roughness Rt) and productivity (material removal rate MRR) when face milling polyoxymethylene (POM C). In this context, the experiments were planned according to the standard orthogonal network of Taguchi L16 (4^3). An analysis of variance (ANOVA) was performed to study the influence of each input factor on the output parameters. The processing of the results made it possible to propose prediction models for the surface. Finally, a mono and multi-objective optimisation was performed using the grey relational analysis (GRA) approach and ranking based on data envelopment analysis (DEAR) coupled with the Taguchi method based on the signal-to-noise ratio (S/N). ANOVA results revealed that feed per tooth (fz) has the greatest influence on (Ra, Rt, and MRR), with successive contributions of (97.69, 97.05, and 66.26)%. On the other hand, GRA and DEAR resulted in the same cutting regime (Vc = 251.2 m/min, fz = 0.004 mm/tooth, and ap = 6 mm), leading to optimised responses (Ra = 1.67 µm and MRR = 11.51 cm3/min).