Multi-objective optimization of cutting parameters in high-speed milling based on grey relational analysis coupled with principal component analysis
1. Graduate University of the Chinese Academy of Sciences, Beijing 100049, China
2. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
This paper investigates optimization problem of the cutting parameters in high-speed milling on NAK80 mold steel. An experiment based on the technology of Taguchi is performed. The objective is to establish a correlation among spindle speed, feed per tooth and depth of cut to the three directions of cutting force in the milling process. In this study, the optimum cutting parameters are obtained by the grey relational analysis. Moreover, the principal component analysis is applied to evaluate the weights so that their relative significance can be described properly and objectively. The results of experiments show that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of cutting parameters and the proposed approach can be a useful tool to reduce the cutting force.