论文:2023,Vol:41,Issue(1):198-208
引用本文:
李春磊, 常智勇, 李亮. 一种新的基于信息熵和PSO-Kmeans聚类算法的典型工艺路线发现与重用体系[J]. 西北工业大学学报
LI Chunlei, CHANG Zhiyong, LI Liang. A novel system for discovery and reuse of typical process route based on information entropy and PSO-Kmeans clustering algorithm[J]. Journal of Northwestern Polytechnical University

一种新的基于信息熵和PSO-Kmeans聚类算法的典型工艺路线发现与重用体系
李春磊1,2, 常智勇3, 李亮1,2
1. 宝鸡文理学院 机械工程学院, 陕西 宝鸡 721016;
2. 陕西省机器人关键零部件先进制造与评估省市共建重点实验室, 陕西 宝鸡 721016;
3. 西北工业大学 机电学院, 陕西 西安 710072
摘要:
制造企业在经营和发展过程中会积累大量的制造实例,对这些实例资源进行合理地挖掘和重用,是提高制造效率和支持创新的最有效途径之一。为了科学确定重用对象和提高重用灵活性,提出了一种基于信息熵和PSO-Kmeans聚类算法的典型工艺路线发现与重用体系。在该体系下,提出了一种基于多级最长公共子序列信息熵的机加工艺路线相似度度量方法。在此基础上,提出了一种基于谱聚类思想和PSO-Kmeans聚类算法的典型工艺路线发现方法,并分析讨论了2种基于典型工艺路线的机加工艺重用途径。通过3个验证实例,说明所提出的体系可以更好地支持制造实例重用。
关键词:    制造实例重用    典型工艺路线    相似性度量    信息熵    PSO-Kmeans聚类算法   
A novel system for discovery and reuse of typical process route based on information entropy and PSO-Kmeans clustering algorithm
LI Chunlei1,2, CHANG Zhiyong3, LI Liang1,2
1. School of Mechanical Engineering, Baoji University of Arts and Sciences, Baoji 721016, China;
2. Shaanxi Key Laboratory of Advanced Manufacturing and Evaluation of Robot Key Components, Baoji 721016, China;
3. School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
Manufacturing enterprises will accumulate a large number of manufacturing instances as they run and develop. Being able to excavate and reuse the instance resources reasonably is one of the most effective ways to improve manufacturing and support innovation. To determine the reuse object scientifically and raise the reuse flexibility, a novel system for discovery and reuse of typical process route based on the information entropy and PSO-Kmeans clustering algorithm is proposed in this paper. In this system, a similarity measurement method of machining process routes based on the information entropy of multistage longest common subsequence is developed. Then a discovery method of typical process route based on the spectral clustering idea and PSO-Kmeans clustering algorithm is invented, and the two reuse approaches based on the typical process route are analyzed and discussed. Finally, the three case studies are rendered and the results reveal that the proposed system can provide better support for manufacture instance reuse.
Key words:    manufacture instance reuse    typical process route    similarity measurement    information entropy    PSO-Kmeans clustering algorithm   
收稿日期: 2022-05-24     修回日期:
DOI: 10.1051/jnwpu/20234110198
基金项目: 陕西省重点研发计划(2022GY-254)、浙江大学CAD&CG国家重点实验室开放课题(A2204)、陕西省教育厅自然科学类专项科研计划(21JK0490)资助
通讯作者: 李亮(1979-),宝鸡文理学院副教授,主要从事机器人技术研究。e-mail:Leeliang@126.com     Email:Leeliang@126.com
作者简介: 李春磊(1987-),宝鸡文理学院讲师,主要从事复杂产品的数字化设计与制造、智能制造研究。
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