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Computational Intelligence and Neuroscience
Volume 2016, Article ID 8289508, 8 pages
Research Article

Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic

1School of Business, Huaihua University, Huaihua, Hunan 418000, China
2School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi 030051, China

Received 20 July 2016; Revised 25 October 2016; Accepted 2 November 2016

Academic Editor: Elio Masciari

Copyright © 2016 Shi-wang Hou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.