Data mining for design for remanufacture

Vijitashwa Pandey, Deborah L Thurston, Yuan Zhao

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


Design for remanufacture and reuse can gain immensely from up-to-date information about manufacturer and customer preferences. Traditionally difficult to gather, data available through purchase records at stores or manufacturer computer systems can now be utilized to make better design decisions. Data mining methods can predict future decisions made by decision makers, based on their past responses to various sets of inputs. In this paper, we first present a model of commonality (inputs) within and across generations of a product and argue that product reuse decisions are contingent on these commonality values. A case study is performed on simulated data and responses (decisions of whether or not to reuse) to commonality inputs and results are presented.

Original languageEnglish (US)
Title of host publicationIIE Annual Conference and Expo 2008
Number of pages6
StatePublished - 2008
EventIIE Annual Conference and Expo 2008 - Vancouver, BC, Canada
Duration: May 17 2008May 21 2008


OtherIIE Annual Conference and Expo 2008
CityVancouver, BC


  • Data mining
  • Design for remanufacture
  • Product line commonality

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Industrial and Manufacturing Engineering


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