Optimization of the red mud–aluminum composite in the turning process by the Grey relational analysis with entropy

Abstract

This paper presents the findings of an experimental investigation on the effects of cutting speed, feed rate, depth of cut, and nose radius in the CNC turning operation performed on red mud-based aluminum metal matrix composites. The surface roughness, flank wear, and power consumption are considered as the output quality characteristics. The Taguchi-based Grey relational analysis with entropy method has been used to accomplish the objective of the experimental study. The entropy method is applied to evaluate the weighting values corresponding to various performance characteristics. The L9 orthogonal array design has been used for conducting the experiments. The Grey relational analysis with entropy reveals that the optimal combination of the machining parameters for the multi-performance characteristics of the red mud-based aluminum is the set of cutting speed of 275 m/min, feed 0.2 mm/rev, depth of cut 0.5 mm, and nose radius 0.4 mm. The optimal results were compared with the experimental results for verifying the approach, and it is observed that the surface roughness decreases from 2.56 to 2.27 µm, tool wear decreases from 0.3 to 0.28 mm, and power consumption decreases from 721 to 715 W.