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Fuzzy outranking approach to prioritize design requirements in quality function deployment

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  • J. Wang

Abstract

Identification of important design requirements for product development is critical because it leads to successful products with shorter development time. The quality function deployment (QFD) is a tool to help the product development team systematically determine the design requirements for developing a product with higher customer satisfaction. However, it is more difficult to assess the performance of a design with accurate quantitative values, due to the imprecise and incomplete information available at the early design stage. A decision model is needed to assist team members in selecting the critical design requirements for product development. This paper considers the QFD planning as a multi-criteria decision problem and proposes a new fuzzy outranking approach to prioritize design requirements recognized in QFD. The inputs required for QFD are represented with linguistic terms that are characterized by fuzzy sets. The fuzzy outranking relation is used to model the imprecise preference relations between design requirements. Consequently, the critical design requirements are identified for the focus of design to achieve not only customer satisfaction but also the balanced design of a product. Moreover, the sensitivity analysis is applied to examine the robustness of the result. Finally, an example of a car design is used to illustrate the approach developed.

Suggested Citation

  • J. Wang, 1999. "Fuzzy outranking approach to prioritize design requirements in quality function deployment," International Journal of Production Research, Taylor & Francis Journals, vol. 37(4), pages 899-916, March.
  • Handle: RePEc:taf:tprsxx:v:37:y:1999:i:4:p:899-916
    DOI: 10.1080/002075499191599
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    1. Tulay Ilhan-Nas & Aysegul Saglam & Tarhan Okan & Iskender Peker, 2024. "The Status of University Business Schools Regarding Industry 4.0: From the Turkish Perspective," SAGE Open, , vol. 14(1), pages 21582440241, March.

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