title: Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic.
abstract: 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.
authors.affiliation: School of Business, Huaihua University, Huaihua, Hunan 418000, China.
authors.forename: Shi-Wang
authors.identifier: 0000-0002-4024-0637
authors.initials: SW
authors.lastname: Hou
authors.affiliation: School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi 030051, China.
authors.forename: Shunxiao
authors.initials: S
authors.lastname: Feng
authors.affiliation: School of Mechanical and Power Engineering, North University of China, Taiyuan, Shanxi 030051, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted; D017143:Fuzzy Logic; D006801:Humans; D007360:Intelligence