Multi-Objective Optimization in End Milling of Al-6061 Using Taguchi Based G-PCA

In this study, a multi objective optimization for end milling of Al 6061 alloy has been presented to provide better surface quality and higher Material Removal Rate (MRR). The input parameters considered for the analysis are spindle speed, depth of cut and feed. The experiments were planned as per Taguchis design of experiment, with L27 orthogonal array. The Grey Relational Analysis (GRA) has been used for transforming multiple quality responses into a single response and the weights of the each performance characteristics are determined by employing the Principal Component Analysis (PCA), so that their relative importance can be properly and objectively described. The results reveal that Taguchi based G-PCA can effectively acquire the optimal combination of cutting parameters.

Authors:

• M. K. Pradhan
• Mayank Meena
• Shubham Sen
• Arvind Singh

Keywords:

• Material Removal Rate
• Surface Roughness
• Taguchi Method
• Grey Relational Analysis
• Principal Component Analysis.

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