Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic
Joint Authors
Hou, Shi-wang
Feng, Shunxiao
Wang, Hui
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-12-12
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Locating the assignable causes by use of the abnormal patterns of control chart is a widely used technology for manufacturing quality control.
If there are uncertainties about the occurrence degree of abnormal patterns, the diagnosis process is impossible to be carried out.
Considering four common abnormal control chart patterns, this paper proposed a characteristic numbers based recognition method point by point to quantify the occurrence degree of abnormal patterns under uncertain conditions and a fuzzy inference system based on fuzzy logic to calculate the contribution degree of assignable causes with fuzzy abnormal patterns.
Application case results show that the proposed approach can give a ranked causes list under fuzzy control chart abnormal patterns and support the abnormity eliminating.
American Psychological Association (APA)
Hou, Shi-wang& Feng, Shunxiao& Wang, Hui. 2016. Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1099787
Modern Language Association (MLA)
Hou, Shi-wang…[et al.]. Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1099787
American Medical Association (AMA)
Hou, Shi-wang& Feng, Shunxiao& Wang, Hui. Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1099787
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099787