Tool Path Optimization for Cone Surface Using Genetic Algorithm

被引:0
|
作者
Van Quy Hoang [1 ]
机构
[1] Hai Phong Univ, Haiphong, Vietnam
来源
PROCEEDINGS OF THE 3RD ANNUAL INTERNATIONAL CONFERENCE ON MATERIAL, MACHINES AND METHODS FOR SUSTAINABLE DEVELOPMENT, VOL 2, MMMS 2022 | 2024年
关键词
Genetic algorithm; TSP; CNC machine; Tool path optimization; GENERATION;
D O I
10.1007/978-3-031-39090-6_65
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In this paper, we introduce a method to optimize toolpaths on 3-axis CNC milling machines when machining parts with conical surfaces. The method is based on a genetic algorithm, in which individuals are encoded by binary strings. Genetic operators such as crossover and mutation are also considered with appropriate requirements. A suitable environment is initialized accordingly to fit individuals and optimize the problem. A script is built on Matlab2010a to determine the best individual, and the results are then simulated on CimCo Edit V7 to evaluate the effectiveness. The results show that our proposed method is entirely feasible, and the optimized toolpaths result in better outcomes than traditional methods.
引用
收藏
页码:587 / 594
页数:8
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