完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Hsu, HM | en_US |
dc.contributor.author | Chen, YK | en_US |
dc.date.accessioned | 2014-12-08T15:44:09Z | - |
dc.date.available | 2014-12-08T15:44:09Z | - |
dc.date.issued | 2001-03-01 | en_US |
dc.identifier.issn | 0956-5515 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1023/A:1008903614042 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/29813 | - |
dc.description.abstract | 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. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | fuzzy reasoning | en_US |
dc.subject | knowledge acquisition | en_US |
dc.subject | diagnosis system | en_US |
dc.subject | process control | en_US |
dc.subject | (X)over-bar control chart | en_US |
dc.title | A fuzzy reasoning based diagnosis system for (X)over-bar control charts | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1023/A:1008903614042 | en_US |
dc.identifier.journal | JOURNAL OF INTELLIGENT MANUFACTURING | en_US |
dc.citation.volume | 12 | en_US |
dc.citation.issue | 1 | en_US |
dc.citation.spage | 57 | en_US |
dc.citation.epage | 64 | en_US |
dc.contributor.department | 工業工程與管理學系 | zh_TW |
dc.contributor.department | Department of Industrial Engineering and Management | en_US |
dc.identifier.wosnumber | WOS:000167499700005 | - |
dc.citation.woscount | 16 | - |
顯示於類別: | 期刊論文 |