Typical process discovery of satellite typical parts based on affinity propagation clustering

被引:0
|
作者
Wang, Lin [1 ]
Zhang, Yongjian [2 ]
Zhong, Shisheng [1 ]
机构
[1] School of Mechatronics Engineering, Harbin Institute of Technology, Harbin,150001, China
[2] School of Naval Architecture and Ocean Engineering, Harbin Institute of Technology at Weihai, Weihai,264209, China
关键词
Affinity propagation - Affinity propagation clustering - Clustering results - Directed graph models - Effectiveness evaluation - Historical process - Process similarities - Similarity measurements;
D O I
10.13196/j.cims.2015.06.008
中图分类号
学科分类号
摘要
Aiming at the problem that a lot of repeated jobs existed in the process planning of satellite typical parts, and many kinds of historical process data were not fully reused, the typical process discovery was researched to improve the utilization of typical process and enhance the process planning efficiency. The discovery problem of typical process was described, and the attributed directed graph model of process was built. The similarity between processes was obtained with the similarity measurement of process cells and process routes. Based on the process similarity, affinity propagation method was used to cluster the process, and the clustering result was evaluated according to Silhouette index and In-Group Proportion (IGP) index to get the best clustering number. The machining process of satellite plate was used as an example to verify the effectiveness of proposed method, and five typical processes were obtained. ©, 2015, CIMS. All right reserved.
引用
收藏
页码:1469 / 1475
相关论文
共 50 条
  • [41] Affinity propagation clustering based on the density of principal components
    Que, Jia-Kai (guyancanyun@qq.com), 1600, Northeast University (35):
  • [42] Classifier ensemble selection based on affinity propagation clustering
    Meng, Jun
    Hao, Han
    Luan, Yushi
    JOURNAL OF BIOMEDICAL INFORMATICS, 2016, 60 : 234 - 242
  • [43] Affinity Propagation Clustering Using Path Based Similarity
    Jiang, Yuan
    Liao, Yuliang
    Yu, Guoxian
    ALGORITHMS, 2016, 9 (03)
  • [44] An improved PSO clustering algorithm based on affinity propagation
    Zheng, Yuyan
    Qu, Jianhua
    Zhou, Yang
    1600, World Scientific and Engineering Academy and Society, Ag. Ioannou Theologou 17-23, Zographou, Athens, 15773, Greece (12): : 447 - 456
  • [45] Subset multiway principal component analysis monitoring for batch process based on affinity propagation clustering
    Hu Y.
    Gao X.
    Li Y.
    Qi Y.
    Wang P.
    Huagong Xuebao/CIESC Journal, 2016, 67 (05): : 1989 - 1997
  • [46] Typical Scenario Generation Algorithm for Microgrid Based on Deep Temporal Clustering
    Zhuang Y.
    Cheng L.
    Qi N.
    Chen W.
    Wu X.
    Yao Z.
    Dianli Xitong Zidonghua/Automation of Electric Power Systems, 2023, 47 (20): : 95 - 103
  • [47] ONE OF THE ADAPTIVE CLUSTERING ALGORITHM BASED ON TYPICAL AND STOCHASTIC DATA SETS
    Jia Changyun
    Jin Liang
    3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND COMPUTER SCIENCE (ITCS 2011), PROCEEDINGS, 2011, : 450 - 452
  • [48] Method of Modulation Recognition of Typical Communication Satellite Signals Based on Cyclostationary
    Li, Shijing
    Wang, Yuwen
    2013 ICME INTERNATIONAL CONFERENCE ON COMPLEX MEDICAL ENGINEERING (CME), 2013, : 268 - 273
  • [49] Estimation of Water-Use Efficiency Based on Satellite for the Typical Croplands
    Wang, Tongxin
    Zhang, Hongyan
    Zhao, Jianjun
    Guo, Xiaoyi
    Tong, Shouzheng
    IEEE ACCESS, 2020, 8 : 220533 - 220541
  • [50] Typical Target Detection In Satellite Images Based On Convolutional Neural Networks
    Wu, Hui
    Zhang, Hui
    Zhang, Jinfang
    Xu, Fanjiang
    2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS, 2015, : 2956 - 2961