Mathematical model of machining parameters optimization for titanium alloy cutting and process parameter analysis

DU Hong-chun1, ZHANG Qi2
(1.Department of Basic Courses,Jiangsu Food & Pharmaceutical Science College,Huaian 223002,China;
2.School of Intelligent Manufacturing, Panzhihua University, Panzhihua 617000, China)

Abstract: Aiming at the deformation of titanium alloy material caused by the unreasonable selection of machining parameters in the process of machining titanium alloy materials, the Kriging surrogate model was proposed to establish the mathematical model between machining parameters and main cutting force of titanium alloy. The accuracy of Kriging model established by different sample data was studied. The influence of four design of experiment methods including boxbehnken design of experiment, orthogonal design of experiment, optimized Latin hypercube design of experiment and fullfactor design of experiment on the accuracy of Kriging model was discussed based on the analysis results of different cutting parameters obtained under the same working condition. Meanwhile, quantum particle swarm optimization with levy was adopted to optimize the variation function parameters of traditional kriging to improve the fitting accuracy of Kriging model based on the best experimental design scheme, and proposed a mathematical model with higher accuracy for the optimization of titanium alloy cutting parameters. The influence of machining parameters on cutting force was discussed based on the established mathematical model. The simulation results indicate that the precision evaluation index of the Kriging model based on quantum particle swarm optimization with levy are improved. The accuracy of the optimized Kriging model has been significantly improved. Feed and tool front angle are negatively correlated with the main cutting force, while cutting speed is positively correlated with the main cutting force.

Key words: parameter optimization; mathematical model; design of experiment; quantum particle swarm optimization；variation function