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

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.