NDLI: Fusion of soft and hard computing for fault diagnosis in manufacturing systems

Content Provider	IEEE Xplore Digital Library
Author	Fries, T.P. Graham, J.H.
Copyright Year	2003
Description	Author affiliation: Comput. Sci. Dept., Coastal Carolina Univ., Conway, SC, USA (Fries, T.P.)
Abstract	The rapid diagnosis of faults in computerized manufacturing systems is crucial to reduce expensive downtime. Many hard computing approaches use either symptom-based or functional reasoning. Symptom-based approaches are unable to handle exceptions, while functional approaches are computationally expensive, and, thus unable to produce a real-time response. Current hybrid approaches which combines the two hard computing methods are too structured in their approach to switching between reasoning methods and, thus fail to provide rapid response comparable to humans. This paper presents a robust, extensible approach to fault diagnosis combines these hard computing methods with the soft computing of agents using fuzzy logic. This fusion of hard and soft computing methods allows unstructured switching between reasoning methods by utilizing multiple intelligent agents which examine the problem domain from a variety of perspectives.
Sponsorship	Syst., Man & Cybernetics Soc. IEEE
Starting Page	114
Ending Page	119
File Size	356787
Page Count	6
File Format	PDF
ISBN	0780379527
ISSN	1062922X
DOI	10.1109/ICSMC.2003.1243801
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer aided manufacturing Fault diagnosis Manufacturing systems Intelligent agent Computer science Humans Robustness Manufacturing automation Centralized control Control systems
Content Type	Text
Resource Type	Article

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