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An Exact Expected Value-Based Method to Prioritize Engineering Characteristics in Fuzzy Quality Function Deployment

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Abstract

Quality function deployment (QFD) is a comprehensive and systematic method that contributes to transforming customer requirements (CRs) into appropriate engineering characteristics (ECs). In QFD, one fundamental and crucial step is to derive the importance of ECs. Since the QFD process involves huge amounts of subjective perceptions or evaluations made by both customers and decision-makers, the importance of ECs naturally becomes fuzzy. This paper focuses on how the importance of ECs can be correctly measured and rated in fuzzy environments, and proposes an approach for deriving the exact expected values and the rankings of the importance of ECs without any simulations or approximations. A design case is also illustrated to show the performance of the proposed method and compare with the traditional h-cut method. The results show that through our method, not only can more reasonable and reliable rankings of ECs be obtained, but also the burden of the complex arithmetic processes which the approximation or simulation algorithms generally involve can be eliminated. Finally, some extensive applications of the exact expected values of the fuzzy importance of ECs are demonstrated including the determination of the overall customer satisfaction and the cost–benefit analysis of ECs.

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Acknowledgments

This work was supported in part by a grant from the National Natural Science Foundation of China (No. 71272177).

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Authors and Affiliations

  1. School of Management, Shanghai University, Shanghai, 200444, China

    Jing Liu, Jian Zhou & Xiajie Yi

  2. School of Management, Shenzhen Polytechnic, Shenzhen, 518055, China

    Yizeng Chen

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  1. Jing Liu
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  2. Yizeng Chen
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  3. Jian Zhou
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  4. Xiajie Yi
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Correspondence to Jian Zhou.

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Liu, J., Chen, Y., Zhou, J. et al. An Exact Expected Value-Based Method to Prioritize Engineering Characteristics in Fuzzy Quality Function Deployment. Int. J. Fuzzy Syst. 18, 630–646 (2016). https://doi.org/10.1007/s40815-015-0118-0

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