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dc.contributor.advisorOlwell, David
dc.contributor.authorLee, Hock Guan
dc.dateSep-13
dc.date.accessioned2013-11-20T23:36:15Z
dc.date.available2013-11-20T23:36:15Z
dc.date.issued2013-09
dc.identifier.urihttp://hdl.handle.net/10945/37659
dc.descriptionApproved for public release; distribution is unlimiteden_US
dc.description.abstractEngine failures on ships are expensive, and affect operational readiness critically due to long turn-around times for maintenance. Prior to the engine failures, there are signs of engine characteristic changes, for example, exhaust gas temperature (EGT), to indicate that the engine is acting abnormally. This is used as a precursor towards the modeling of failures. There is a threshold limit of 520 degree Celsius for the EGT prior to the need for human intervention. With this knowledge, the use of time series forecasting technique, to predict the crossing over of threshold, is appropriate to model the EGT as a function of its operating running hours and load. This allows maintenance to be scheduled just in time. When there is a departure of result from the predictive model, Cumulative Sum (CUSUM) Control charts can then be used to monitor the change early before an actual problem arises. This paper discusses and demonstrates the proof of principle for one engine and a particular operating profile of a commercial vessel with the use of predictive analytics. The realization with time series forecasting coupled with CUSUM control chart allows this approach to be extended to other attributes beyond EGT.en_US
dc.description.urihttp://archive.org/details/astudyonpredicti1094537659
dc.publisherMonterey California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleA study on predictive analytics application to ship machinery maintenanceen_US
dc.typeThesisen_US
dc.contributor.secondreaderPapoulias, Fotis
dc.contributor.departmentSystems Engineering (SE)
dc.subject.authorPredictiveen_US
dc.subject.authorPrecursoren_US
dc.subject.authorMachinery Maintenanceen_US
dc.subject.authorFailuresen_US
dc.description.serviceCivilian, Singapore Technologies Marine, Ltd.en_US
etd.thesisdegree.nameMaster Of Science In Systems Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineSystems Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US


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