Warranty prediction during product development: Developing an event generation engine in an engineer-to-order environment

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dc.contributor.advisor Esterman, Marcos
dc.contributor.author Kang, Hee-Rak
dc.date.accessioned 2012-02-06T15:43:20Z
dc.date.available 2012-02-06T15:43:20Z
dc.date.issued 2011-06
dc.identifier.uri http://hdl.handle.net/1850/14672
dc.description.abstract In order for manufacturing companies to stay competitive, it is necessary to drive warranty system improvements in terms of improved product reliability, improved service delivery efficiency and properly designed warranty policies. However, traditional methods for assessing warranty performance are not always sufficient to alert product development teams of the impending warranty issues. Furthermore, improved assessment methods are needed to aid product development teams make decisions related to the warranty performance of the product. The focus of this research was to develop a framework to integrate statistical inference methods and data mining techniques to create a warranty event generation framework. This was done on the context of an engineer-to-order product development environment. The objectives of this work were: (1) to develop an inference model for the integration of disparate data sources; (2) to demonstrate that multiple data streams can be conditioned for input into the above inference model; (3) to develop the above model and process in light of actual data. This thesis will report on the progress and challenges that have been made toward fulfilling these objectives. The thesis closes by outlining the future research agenda for developing a warranty event generation engine that can integrate data from disparate data sources. en_US
dc.language.iso en_US en_US
dc.subject Bayesian en_US
dc.subject Data mining en_US
dc.subject Engineer to order en_US
dc.subject Event generation en_US
dc.subject Warranty en_US
dc.subject.lcc TS170 .K36 2011
dc.subject.lcsh New products--Development en_US
dc.subject.lcsh Warranty en_US
dc.title Warranty prediction during product development: Developing an event generation engine in an engineer-to-order environment en_US
dc.type Thesis en_US
dc.description.college Kate Gleason College of Engineering en_US
dc.description.department Department of Industrial and Systems Engineering en_US

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