Multi-response optimization of machining parameters on red mud-based aluminum metal matrix composites in turning process

This paper presents the findings of an experimental investigation into the effects of cutting speed, feed rate, depth of cut, and nose radius in computer numerical control (CNC) turning operation performed on red mud-based aluminum metal matrix composites. This paper investigates optimization design of a turning process performed on red mud-based aluminum metal matrix composites. The major performance characteristics selected to evaluate the process are surface roughness, power consumption, and vibration, and the corresponding turning parameters are cutting speed, feed, depth of cut, and nose radius. Taguchi-based grey analysis, which uses grey relational grade as performance index, is specifically adopted to determine the optimal combination of turning parameters. The principal component analysis (PCA) is applied to evaluate the weighting values corresponding to various performance characteristics. L9 orthogonal array design has been used for conducting the experiments. The outcome of confirmation experiments reveals that grey relational analysis coupled with PCA can effectively be used to obtain the optimal combination of turning parameters. Hence, this confirms that the proposed approach in this study can be a useful tool to improve the turning performance of red mud-based aluminum metal matrix composites in CNC turning process.