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| Cutting Parameters Optimization of Titanium Alloy Milling Process Based on Support Vector Machine and Particle Swarm Algorithm |
| XIANG Guoqi1， YIN Guofu2 |
（1. School of Resources and Environmental Engineering, Panzhihua University, Panzhihua 617000, China;
2. School of Manufacturing Science and Engineering, Sichuan University, Chengdu 610054, China） |
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Abstract Titanium alloys are widely used in aviation fields, the processing quality of this materials will be affected
by the milling force. In order to guarantee the machining quality, improve production efficiency and reduce cost, the cutting
parameters of the titanium alloy are reasonable selected, which play an important role. In this paper, the titanium alloy
Ti6Al4V milling process is analyzed by finite element method, a milling force prediction model is established based on support
vector machine (SVM). The design methodology based on SVM and particle swarm optimization (PSO) is proposed
for titanium alloy milling process cutting parameters. The results show that this methodology is feasible and highly effective,
and thus can be used in the machining process parameters optimum and other material processing fields.
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2016, 
