NDLI: Study on multi-agent based maintenance decision support system used for power plant equipment

Content Provider	IEEE Xplore Digital Library
Author	Yu-jiong Gu Xiao-feng Dong Jian-jun Wu Kun Yang
Copyright Year	2008
Description	Author affiliation: Sch. of Energy & Power Eng., North China Electr. Power Univ., Beijing, China (Yu-jiong Gu; Xiao-feng Dong; Jian-jun Wu; Kun Yang)
Abstract	With the developing of industry, maintenance has become an important factor that influences survival and development of the business. There are numerous pieces of equipment in a power plant, but the maintenance requirement is different for respective equipment, so making condition based maintenance in a power plant is a systemic and integrative activity in maintenance management. As an interdisciplinary activity, a special maintenance decision support system is necessary to aid operating and maintenance personnel use that knowledge right and well. As a hotspot of Distributed Artificial Intelligence research, agent technology is one of the strongest tools for constituting large-scale distributed and open computer-based systems. This paper briefly introduces decision support system and agent technology, and presents an architecture of multiagent based maintenance decision support system used for power plant equipment, and describes its architecture, function and decision making process in detail.
Starting Page	2167
Ending Page	2171
File Size	628353
Page Count	5
File Format	PDF
ISBN	9781424426294
DOI	10.1109/IEEM.2008.4738255
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-08
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision support systems Agent Power system management Decision support system Decision making Condition based maintenance Personnel Distributed computing Computer architecture Large-scale systems Energy management Artificial intelligence Power generation
Content Type	Text
Resource Type	Article

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