Multi-Objective Optimization Strategy for Cutting Parameters Based on Controlling Face Milling Distortion

Abstract

Machining distortion analysis and control are the kernel problem in manufacturing industry recently. This paper take face milling as research object, a finite element model for 3D milling process is set up based on some key techniques including cutter feed trajectories representations, cutter tooth-workpiece engagement model etc; Then the optimum LS-SVM model which can express the transitive relationship between cutting parameters and distortion error is set up; The cutting parameters optimization model based on controlling the machining distortion is founded by seeing the optimum LS-SVM model as the main objective function, meanwhile, an effective multi-objective optimization algorithm is proposed by coupling particle swarm algorithm and gray relevancy analysis, this algorithm can change the multi-objective optimization problem into optimizing the gray relevancy value effectively. As an example, the feasibility of proposed machining distortion controlling approach is verified.