revision paper for engineering

May 15th, 2015
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Data Mining to Support Engineering DesignDecisionsPooja Jadhav, Sylvia C Wong, Gary B Wills, Richard M Crowder and Nigel RShadboltSchool of Electronics and Computer Science,University of Southampton, UK{sw2, gbw, rmc, nrs} at The design and maintenance of an aero-engine generates asignificant amount of documentation. When designing new engines, engineers must obtain knowledge gained from maintenance of existing enginesto identify possible areas of concern. Firstly, this paper investigate theuse of advanced business intelligence tenchniques to solve the problemof knowledge transfer from maintenance to design of aeroengines. Basedon data availability and quality, various models were deployed. An association model was used to uncover hidden trends among parts involvedin maintenance events. Classification techniques comprising of variousalgorithms was employed to determine severity of events. Causes of highseverity events that lead to major financial loss was traced with the helpof 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 supporton RDF/OWL-based warehoused data.1IntroductionThe design and maintenance of large and complex engineering systems requires asignificant amount of documentation, particularly if the system

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