A data mining based clustering approach to group technology

Mu-Chen Chen*, Hsiao Pin Wu, Chia Ping Lin

*Corresponding author for this work

研究成果: Conference article同行評審

1 引文 斯高帕斯(Scopus)

摘要

Cellular manufacturing is an essential application of group technology (GT) in which families of parts are produced in manufacturing cells. This paper describes the development of a cell formation approach based on association rule mining and 0-1 integer programming. It is valuable to find the important associations among machines such that the occurrence of some machines in a machine cell will cause the occurrence of other machines in the same cell. A clustering model using the discovered association data is formulated to maximize the closeness measures among machines within each cell. From the results of three medium-sized problems, the proposed approach shows its ability to find quality solutions of cell formation problems.

原文English
頁(從 - 到)3554-3558
頁數5
期刊Proceedings - IEEE International Conference on Robotics and Automation
3
DOIs
出版狀態Published - 9 十二月 2003
事件2003 IEEE International Conference on Robotics and Automation - Taipei, Taiwan
持續時間: 14 九月 200319 九月 2003

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