Abstract

Given the serious work hardening phenomenon, high chemical activity, severe tool wear, and poor workpiece surface quality during the cutting of titanium alloys, placing micro-texture on the tool surface decreases the tool-chip contact area and friction and plays the role of wear resistance and friction reduction. In order to improve the cutting performance of cutting tools, the present study examins the effect of micro-texture parameters of a cemented carbide ball-end milling cutter on cutting force, tool wear, and workpiece surface roughness and establishes a regression analysis model via regression analysis. We consider the cutting performance of a cemented carbide micro-texture ball-end milling cutter as an evaluation standard. A genetic algorithm is applied to the multi-objective optimization of micro-texture parameters, and a regression analysis model of micro-texture design criteria is established. This provides a standardised reference to select standard micro-texture parameters in the design and preparation of a cemented carbide micro-texture ball-end milling cutter.

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