文献类型：期刊文献

英文题名：A novel fuzzy linguistic model for prioritising engineering design requirements in quality function deployment under uncertainties

作者：Yan, Hong-Bin[1];Ma, Tieju[1];Li, Yashuai[2]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Kowloon, Hong Kong, Peoples R China

年份：2013

卷号：51

期号：21

起止页码：6336

外文期刊名：INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

收录：;EI(收录号：20134717012923);WOS:【SSCI(收录号:WOS:000326071700003)，SCI-EXPANDED(收录号:WOS:000326071700003)】；

基金：We would like to appreciate constructive comments and valuable suggestions from anonymous referees, which have helped us efficiently improve the quality of this paper. This study was partly supported by the National Natural Sciences Foundation of China (NSFC) under Grants #71101050, #71125002, sponsored by Shanghai Pujiang Program, the Program for New Century Excellent Talents in University (NCET-09-0345), Fok Ying-Tong Education Foundation under Grant #131082 and the Fundamental Research Funds for the Central Universities in China under Grant #WN1123002.

语种：英文

外文关键词：QFD; engineering design requirements; fuzzy linguistic approach; order-based semantics; fuzzy preference relations

摘要：Quality function deployment (QFD) is a planning and problem-solving tool gaining wide acceptance for translating customer requirements (CRs) into the design requirements (DRs) of a product. Deriving the priority order of DRs from input variables is a crucial step in applying QFD. Due to the inherent vagueness or impreciseness in QFD, the use of fuzzy linguistic variables for prioritising DRs has become more and more important in QFD applications. Existing approaches make use of the associated fuzzy membership functions of linguistic labels based on the fuzzy extension principle. However, an inherent limitation of such fuzzy linguistic approaches is the information loss caused by approximation processes, which eventually implies a lack of precision in the final results. This paper proposes an alternative approach to prioritising engineering DRs in QFD based on the order-based semantics of linguistic information and fuzzy preference relations of linguistic profiles, under random interpretations of customers, design team and CRs. Ultimately, this approach enhances the fuzzy-computation-based models proposed in the previous studies by overcoming the mentioned limitations. A case study taken from the literature is used to illuminate the proposed technique and to compare with the previous techniques based on fuzzy computation.