Abstract

Titanium alloys are difficult-to-machine materials that exhibit a low machining efficiency, yielding its restricted applications. The combination of micro-textures and a cemented carbide surface cutter can effectively improve the cutting performance and enhance titanium alloys' machining quality. Therefore, this manuscript investigates a cemented carbide ball-end milling cutter with surface modifications. Firstly, we prepared micro-textures with a variable distribution density on the surface of a cemented carbide cutter and revealed its properties from the microscopic aspect based on the simulation and test methods. Secondly, a milling test was done to reveal the anti-wear and anti-friction properties accuracy. Finally, based on the test data, the Lasso regression prediction models were established. Based on the Matlab particle swarm optimization algorithm, the parameters of micro-textures with a variable distribution density were optimized.

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