Multi-Objective Optimization of Surface Roughness, Cutting Force, and Temperature in Ultrasonic-Vibration-Assisted Milling of Titanium Alloy

作者：Gaofeng Hu, Yanjie Lu, Shengming Zhou, Xin He, Fenghui Zhang, Peng Zhu, Mingliang Wang, Taowei Tan, Guangjun Chen · 发表于：Micromachines · 年份：2025 · DOI：10.3390/mi16080936 · 被引用次数：6 · 研究领域：Advanced machining processes and optimization、Advanced Machining and Optimization Techniques、Advanced Surface Polishing Techniques

Titanium alloys (Ti-6Al-4V) are widely used in the aerospace field. However, as a typical difficult-to-machine material, titanium alloys have a low thermal conductivity, a high chemical activity, and a significant adiabatic shear effect. In conventional milling (CM), the temperature in the cutting zone rises sharply, leading to tool adhesion, rapid wear, and damage to the workpiece surface. This article systematically investigated the influence of process parameters on the surface roughness, cutting force, and cutting temperature in the ultrasonic-vibration-assisted milling (UAM) process of titanium alloys, based on which multi-objective optimization process of the milling process parameters was conducted, by utilizing the grey relational analysis method. An orthogonal experiment with four factors and four levels was conducted. The effects of various process parameters on the surface roughness, cutting force, and cutting temperature were systematically analyzed for both UAM and CM. The grey relational analysis method was employed to transform the optimization problem of multiple process target parameters into a single-objective grey relational degree optimization problem. The optimized parameter combination was as follows: an ultrasonic amplitude of 6 μm, a spindle speed of 6000 rpm, a cutting depth of 0.20 mm, and a feed rate of 200 mm/min. The experimental results indicated that the surface roughness Sa was 0.268 μm, the cutting temperature was 255.39 °C, the cutting force ...