Sm. El-shal et As. Morris, A fuzzy expert system for fault detection in statistical process control of industrial processes, IEEE SYST C, 30(2), 2000, pp. 281-289
Citations number
13
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS
Little work has previously been reported on the use of fuzzy logic within s
tatistical process control when this is used for fault detection as part of
quality control systems in industrial manufacturing processes. Therefore,
this paper investigates the potential use of fuzzy logic to enhance the per
formance of statistical process control (SPC). The cumulative sum of the de
viation in the monitored parameter is combined with the deviation in an att
empt to discriminate between false alarms and real faults and, consequently
, to improve the quality of the solution. Combinations of control rules are
utilized and trained to cope with different inputs such that rejection of
false alarms is achieved and quick detection of real faults is obtained. Th
e design and implementation of this fuzzy expert system (FES) are presented
, and a comparative rule-based study is performed.