A comprehensive end-of-life strategy decision making approach to handle uncertainty in the product design stage

Junfeng Ma, Gul E.Okudan Kremer, Charles David Ray

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

This study employs fuzzy logic to evaluate uncertain component end-of-life (EOL) options in the design stage. Determining EOL strategies during the product design stage can be complex. For example, EOL strategies for retired bicycle components are various and may change with geographic location. Thus, adopting fixed EOL strategies in the product design stage may not always be appropriate; the element of uncertainty should be considered. Limited research has examined uncertainty of EOL strategies during the design stage. Moreover, the evaluation of EOL strategies in a comprehensive manner has not been shown in a realistic case study. These facts motivate this investigation. Fourteen evaluation criteria are used to generate a comprehensive framework for assessing seven EOL strategies. The evaluation process generates the likelihood for each of these strategies by aggregating fuzzy set operations and a left–right fuzzy ranking method. Using SUMPRODUCT calculation for these weights/probabilities and input sustainability value (i.e., cost, environmental impact and labor time), expected values are derived to represent the sustainability values for each EOL strategy. A Technique-for-Order-of-Preference-by-Similarity-to-Ideal-Solution (TOPSIS) based method is employed to identify the appropriate EOL strategy for each component/product. A refrigerator is used as a case study to illustrate the methodology. This study addresses the uncertainty involved in identifying an EOL strategy for a specific product component during the design stage through the use of fuzzy logic. The method closes a gap in the current EOL strategy assessment criteria and introduces a comprehensive evaluation framework to capture multiple strategic perspectives by incorporating 14 key evaluation criteria.

Original languageEnglish (US)
Pages (from-to)469-487
Number of pages19
JournalResearch in Engineering Design
Volume29
Issue number3
DOIs
StatePublished - Jul 1 2018

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Architecture
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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