关键词: 工艺相似度, 设计结构矩阵, 智能聚类, 粒子群算法, 典型工艺路线

Abstract: Aiming at the problems of enterprise process data and knowledge mining, a method of extracting product typical process routs based on intelligent clustering analysis was presented. A similarity factor between two process routs was established and a multi-level comprehensive measurement method for calculating the similarity between two process routs was proposed. Based on the similarity calculation, a process rout design structure matrix was constructed and the noise reduction processing was applied to the matrix data. To reduce the difficulty and complexity of clustering division, the particle swarm optimization was used to realize the intelligent clustering division of process rout design structure matrix. The typical process routs were extracted from the clustering clusters consequently. A mechanical press enterprise was taken as an example to extract typical process routs from the process data, and the effectiveness of proposed method was verified.

Key words: process similarity, design structure matrix, intelligent clustering, particle swarm optimization, typical process rout