IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v58y2020i19p5751-5768.html
   My bibliography  Save this article

Technical attribute prioritisation in QFD based on cloud model and grey relational analysis

Author

Listed:
  • Xu Wang
  • Hong Fang
  • Wenyan Song

Abstract

Promptly development of new products can be achieved through quality function deployment (QFD) process, which is critical to companies’ survival. Since the multi-criteria decision-making problem involved in QFD, a novel method integrating cloud model and grey relational analysis is put forward in this paper. Taking into account the subjectivity and ambiguity in linguistic evaluations, some scholars utilise fuzzy theory, rough theory, interval-valued fuzzy-rough sets and MCDM methods to improve traditional QFD. However, much priori information requirements, inability to handle subjectivity and randomness, and lack of mechanism to overcome small sample size problem are some inevitable drawbacks in these methods. To solve these deficiencies, a hybrid methodology is proposed in this paper, integrating the fortes of cloud model in processing ambiguity and randomness, and the merits of grey relational analysis in overcoming small sample size error as well as revealing the inner correlations. The comparative analysis of different approaches as well as the sensitivity analysis of criteria weights is implemented to prove the stability of the novel method. The results obtained in this paper shows that the proposed method can be a practical tool for improving the efficiency and accuracy of traditional QFD in reality management.

Suggested Citation

  • Xu Wang & Hong Fang & Wenyan Song, 2020. "Technical attribute prioritisation in QFD based on cloud model and grey relational analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 58(19), pages 5751-5768, October.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:19:p:5751-5768
    DOI: 10.1080/00207543.2019.1657246
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2019.1657246
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2019.1657246?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiang, Lei & Wu, Huazhang & Song, Yang, 2022. "Diversified demand for health tourism matters: From a perspective of the intra-industry trade," Social Science & Medicine, Elsevier, vol. 293(C).
    2. Chih-Hung Hsu & Ru-Yue Yu & An-Yuan Chang & Wan-Ling Liu & An-Ching Sun, 2022. "Applying Integrated QFD-MCDM Approach to Strengthen Supply Chain Agility for Mitigating Sustainable Risks," Mathematics, MDPI, vol. 10(4), pages 1-41, February.
    3. Chih-Hung Hsu & Xu He & Ting-Yi Zhang & An-Yuan Chang & Wan-Ling Liu & Zhi-Qiang Lin, 2022. "Enhancing Supply Chain Agility with Industry 4.0 Enablers to Mitigate Ripple Effects Based on Integrated QFD-MCDM: An Empirical Study of New Energy Materials Manufacturers," Mathematics, MDPI, vol. 10(10), pages 1-35, May.
    4. Jia Huang & Ling-Xiang Mao & Hu-Chen Liu & Min-shun Song, 2022. "Quality function deployment improvement: A bibliometric analysis and literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1347-1366, June.
    5. Hua Shi & Ling-Xiang Mao & Ke Li & Xiang-Hu Wang & Hu-Chen Liu, 2022. "Engineering Characteristics Prioritization in Quality Function Deployment Using an Improved ORESTE Method with Double Hierarchy Hesitant Linguistic Information," Sustainability, MDPI, vol. 14(15), pages 1-19, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:58:y:2020:i:19:p:5751-5768. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.