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Data Mining to Support Engineering Design Decision

Record type: Conference or Workshop Item (Paper)

The design and maintenance of an aero-engine generates a significant amount of documentation. When designing new engines, engineers must obtain knowledge gained from maintenance of existing engines to identify possible areas of concern. Firstly, this paper investigate the use of advanced business intelligence tenchniques to solve the problem of knowledge transfer from maintenance to design of aeroengines. Based on data availability and quality, various models were deployed. An association model was used to uncover hidden trends among parts involved in maintenance events. Classification techniques comprising of various algorithms was employed to determine severity of events. Causes of high severity events that lead to major financial loss was traced with the help of summarization techniques. Secondly this paper compares and evaluates the business intelligence approach to solve the problem of knowledge transfer with solutions available from the Semantic Web. The results obtained provide a compelling need to have data mining support on RDF/OWL-based warehoused data.

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Citation

Jadhav, Pooja, Wong, Sylvia C, Wills, Gary B, Crowder, Richard M and Shadbolt, Nigel R (2007) Data Mining to Support Engineering Design Decision At Workshop on Semantic Web and Web 2.0 in Architectural, Product and Engineering Design.

More information

Published date: November 2007
Additional Information: Event Dates: 11 November 2007
Venue - Dates: Workshop on Semantic Web and Web 2.0 in Architectural, Product and Engineering Design, 2007-11-11
Organisations: Web & Internet Science, Agents, Interactions & Complexity, Electronic & Software Systems

Identifiers

Local EPrints ID: 264807
URI: http://eprints.soton.ac.uk/id/eprint/264807
PURE UUID: add8f779-abb0-400c-accb-0fd05b9a5c04
ORCID for Gary B Wills: ORCID iD orcid.org/0000-0001-5771-4088

Catalogue record

Date deposited: 12 Nov 2007 23:48
Last modified: 18 Jul 2017 07:32

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