A methodology for knowledge discovery to support product family design

Seung Moon (), Timothy Simpson () and Soundar Kumara

Annals of Operations Research, 2010, vol. 174, issue 1, 218 pages

Abstract: This paper introduces a methodology for knowledge discovery related to product family design that integrates an ontology with data mining techniques. In the proposed methodology, the ontology represents attributes for the components of products in functional hierarchies. Fuzzy clustering is employed for data mining to first partition product functions into subsets for identifying modules in a given product family and then identify the similarity level of components in a module. Module categorization is introduced to support association rule mining for knowledge discovery related to platform design. We apply the proposed methodology to first develop and then utilize design knowledge for a family of power tools. Based on the developed design knowledge, a new platform is suggested to improve commonality in the power tool family. Copyright Springer Science+Business Media, LLC 2010

Keywords: Data mining; Knowledge discovery; Ontology; Product family and platform design (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10479-008-0349-7

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