Prediction of Optimal Tool Path for Drilling Based on Ant Colony Algorithm

被引:0
|
作者
Van Quy Hoang [1 ]
Xuan Dung Pham [2 ]
Minh Son Nguyen [1 ]
机构
[1] Hai Phong Univ, Haiphong, Vietnam
[2] Hanoi Univ Sci & Technol, Hanoi, 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
Drilling; Ant colony optimization; TSP; CNC machine; Tool path;
D O I
10.1007/978-3-031-39090-6_30
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Fierce competition in the mechanical engineering industry requires manufacturing companies to optimize production. One of the factors that play an essential role in optimizing production is optimizing machining time. In general, the public process can do the job automatically by numerical machine control (CNC). Therefore, optimizing the guide engine can decrease its time value, resulting in increased power. In this search, we focus on using a drilling or laser tool on large metal sheets to create surface patterns using algorithmic architecture (ACO). The algorithm is implemented using Matlab 2010a. Simulation processes on Matlab and CIMCoEdit V7 software. The results show that the algorithm works well and generates a more efficient navigation tool than the conventional method. It is also possible to develop this algorithm for other machining methods, such as hole drilling, electric discharge machining, or plasma.
引用
收藏
页码:261 / 269
页数:9
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