Study on milling behavior of TiAlN coated tool with variable distribution density micro-texture

Abstract

Considering that after milling titanium alloy with a ball-end milling cutter, the wear degree of different areas of the rake face is different, which indicates that the tool-chip contact conditions in this area are different, and then the micro-texture action mode is different. To improve the effect of micro-texture, this paper establishes a mathematical distribution model of variable distribution density micro-texture based on the two-zone method, builds a variable distribution density micro-texture ball-end milling titanium alloy test platform, studies the influence of variable density micro-texture parameters on tool milling behavior, and optimizes the parameters based on the improved particle swarm optimization algorithm. The results show that the micro-texture with variable distribution density has a positive effect on the milling behavior of the tool. The micro-texture parameters of the stickiness area have the greatest influence on the milling behavior of the tool. A texture parameter is optimized, and the overall milling behavior of the variable density micro-texture TiAlN coated milling cutter is optimal. This study provides a theoretical basis for the design and preparation of variable distribution density micro-textured tools. Highlights Based on the two-zone method, the mathematical distribution model of the variable distribution density micro-texture of the rake face of the tool is constructed. The influence mechanism of micro-texture parameters on the milling behavior of a ball-end milling cutter is explored. The multi-objective optimization of the variable density micro-texture parameters was carried out, and the optimal parameter combination was obtained. It is verified that the variable distribution density of the micro-texture has a positive effect on the cutting performance of the tool.