Data mining and fuzzy clustering to support product family design

Research output: Chapter in Book/Report/Conference proceedingConference contribution

35 Scopus citations

Abstract

In mass customization, data mining can be used to extract valid, previously unknown, and easily interpretable information from large product databases in order to improve and optimize engineering design and manufacturing process decisions. A product family is a group of related products based on a product platform, facilitating mass customization by providing a variety of products for different market segments cost-effectively. In this paper, we propose a method for identifying a platform along with variant and unique modules in a product family using data mining techniques. Association rule mining is applied to develop rules related to design knowledge based on product function, which can be clustered by their similarity based on functional features. Fuzzy c-means clustering is used to determine initial clusters that represent modules. The clustering result identifies the platform and its modules by a platform level membership function and classification. We apply the proposed method to determine a new platform using a case study involving a power tool family.

Original languageEnglish (US)
Title of host publicationProceedings of 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006
StatePublished - Nov 29 2006
Event2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006 - Philadelphia, PA, United States
Duration: Sep 10 2006Sep 13 2006

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume2006

Other

Other2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006
CountryUnited States
CityPhiladelphia, PA
Period9/10/069/13/06

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All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

Moon, S. K., Tirupatikumara, S. R., & Simpson, T. W. (2006). Data mining and fuzzy clustering to support product family design. In Proceedings of 2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006 (Proceedings of the ASME Design Engineering Technical Conference; Vol. 2006).