標題: A fuzzy reasoning based diagnosis system for (X)over-bar control charts
作者: Hsu, HM
Chen, YK
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: fuzzy reasoning;knowledge acquisition;diagnosis system;process control;(X)over-bar control chart
公開日期: 1-三月-2001
摘要: This paper describes a new diagnosis system, which is based on fuzzy reasoning to monitor the performance of a discrete manufacturing process and to justify the possible causes. The diagnosis system consists chiefly of a knowledge bank and a reasoning mechanism. The knowledge bank provides knowledge of the membership functions of unnatural symptoms that are described by Nelson's rules on (X) over bar control charts and knowledge of cause-symptom relations. We develop an approach called maximal similarity method (MSM) for knowledge acquisition to construct the fuzzy cause-symptom relation matrix. Through the knowledge bank, the diagnosis system can first determine the degrees of an observation fitting each unnatural symptom. Then, using the fuzzy cause-symptom relation matrix, we can diagnose the causes of process instability. In conclusion we provide a numerical example to illustrate the system.
URI: http://dx.doi.org/10.1023/A:1008903614042
http://hdl.handle.net/11536/29813
ISSN: 0956-5515
DOI: 10.1023/A:1008903614042
期刊: JOURNAL OF INTELLIGENT MANUFACTURING
Volume: 12
Issue: 1
起始頁: 57
結束頁: 64
顯示於類別:期刊論文


文件中的檔案:

  1. 000167499700005.pdf