Multi-Objective Optimization in CNC Turning of S45C Carbon Steel using Taguchi and Grey Relational Analysis Method

Abstract

The optimization of single performance characteristics has been successfully reported by many researchers. However, the multi-objective optimization is more difficult and challenging to be studied due to its complexity. This is because an improvement of one performance characteristic may lead to the degradation of other performance characteristic. In response to that, the study of multiobjective optimization in CNC turning of S45C carbon steel by using Taguchi and Grey Relational Analysis (GRA) method is reported in this paper. Based on grey relational analysis, a grey relational grade (GRG) is computed to optimize the CNC turning process with multiple performance characteristics which are surface roughness, material removal rate (MRR) and tool wear. In this study, two important parameters were selected, namely spindle speed and feed rate while the depth of cut was fixed. The experimental results show that machining parameter in CNC turning can be improved by using this approach.