ITC/USA 2008 Conference Proceedings / The Forty-Fourth Annual International Telemetering Conference and Technical Exhibition / October 27-30, 2008 / Town and Country Resort & Convention Center, San Diego, California / Predictive maintenance is the combination of inspection and data analysis to perform maintenance when the need is indicated by unit performance. Significant cost savings are possible while preserving a high level of system performance and readiness. Identifying predictors of maintenance conditions requires expert knowledge and the ability to process large data sets. This paper describes a novel use of constraint-based data-mining to model exceedence conditions. The approach extends the extract, transformation, and load process with domain aggregate approximation to encode expert knowledge. A data-mining workbench enables an expert to pose hypotheses that constrain a multivariate data-mining process.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/606187 |
| Date | 10 1900 |
| Creators | Gorman, Joe, Takata, Glenn, Patel, Subhash, Grecu, Dan |
| Contributors | Charles River Analytics |
| Publisher | International Foundation for Telemetering |
| Source Sets | University of Arizona |
| Language | en_US |
| Detected Language | English |
| Type | text, Proceedings |
| Rights | Copyright © held by the author; distribution rights International Foundation for Telemetering |
| Relation | http://www.telemetry.org/ |
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