A novel system for discovery and reuse of typical process route based on information entropy and PSO-Kmeans clustering algorithm

Q3 Engineering
Chunlei Li, Zhiyong Chang, Liang Li
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引用次数: 0

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.
基于信息熵和PSO-Kmeans聚类算法的典型工艺路线发现与复用系统
制造业企业在经营和发展过程中会积累大量的制造实例。能够合理地挖掘和重用实例资源是提高制造业水平和支持创新的最有效途径之一。为了科学地确定重用对象,提高重用灵活性,本文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和重用系统。在该系统中,提出了一种基于多级最长公共子序列信息熵的加工工艺路线相似度测量方法。然后,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,并对基于典型工艺路线的两种重用方法进行了分析和讨论。最后,对三个实例进行了研究,结果表明,该系统能够为制造实例复用提供更好的支持。
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来源期刊
西北工业大学学报
西北工业大学学报 Engineering-Engineering (all)
CiteScore
1.30
自引率
0.00%
发文量
6201
审稿时长
12 weeks
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