IDS: Improving Aircraft Fleet Maintenance

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TypeArticle
ConferenceProceedings of the 14th National Conference on Aritificial Intelligence and Innovative Applications of Artificial Intelligence (IAAI-97), July 27-31, 1997., Providence, Rhode Island, USA
Subjectartificial intelligence; fleet maintenance; case-based reasoning; rule-based reasoning
AbstractThis paper describes the Integrated Diagnostic System (IDS), an applied AI project concerned with the development of hybrid information systems to diagnose problems and help manage repair processes of commercial aircraft fleets. A study at one major airline indicated that significant benefits could accrue (approximately 2 percent of overall maintenance budget) through the use of innovative information technology. The IDS prototype (currently in extended field trial) takes as input a stream of messages representing maintenance and diagnostic events. These are filtered and aggregated in order to yield information in an appropriate form for various decision making tasks (and in particular for the maintenance staff while performing fault isolation and repair procedures). IDS was built using ART*Enterprise(r) and makes extensive use of its rule-based and case-based reasoning facilities in order to apply various sources of knowledge (manuals, heuristics, historical data) to this problem. As well as technical issues, this paper discusses the motivation for and methodology followed in this project.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number40181
NPARC number5763089
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Record identifier04d870fe-7043-4a5b-95fa-4201c2187c82
Record created2009-03-29
Record modified2016-05-09
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