文献类型：期刊文献

英文题名：A group decision-making approach to uncertain quality function deployment based on fuzzy preference relation and fuzzy majority

作者：Yan, Hong-Bin[1];Ma, Tieju[1]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China

年份：2015

卷号：241

期号：3

起止页码：815

外文期刊名：EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

收录：;EI(收录号：20145100328564);WOS:【SSCI(收录号:WOS:000347605100022)，SCI-EXPANDED(收录号:WOS:000347605100022)】；

基金：We would like to appreciate constructive comments and valuable suggestions from the three 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 grant nos. 71101050, 71125002, and 71471063; sponsored by the Shanghai Pujiang Program and the Innovation Program of Shanghai Municipal Education Commission under grant no. 14ZS060; and supported by the Fundamental Research Funds for the Central Universities in China under grant no. WN1424004.

语种：英文

外文关键词：Quality management; Uncertain QFD; Group decision-making approach; Fuzzy preference relation; Fuzzy majority

摘要：Quality function deployment (QFD) is one of the very effective customer-driven quality system tools typically applied to fulfill customer needs or requirements (CRs). It is a crucial step in QFD to derive the prioritization of design requirements (DRs) from CRs for a product. However, effective prioritization of DRs is seriously challenged due to two types of uncertainties: human subjective perception and customer heterogeneity. This paper tries to propose a novel two-stage group decision-making approach to simultaneously address the two types of uncertainties underlying QFD. The first stage is to determine the fuzzy preference relations of different DRs with respect to each customer based on the order-based semantics of linguistic information. The second stage is to determine the prioritization of DRs by synthesizing all customers' fuzzy preference relations into an overall one by fuzzy majority. Two examples, a Chinese restaurant and a flexible manufacturing system, are used to illustrate the proposed approach. The restaurant example is also used to compare with three existing approaches. Implementation results show that the proposed approach can eliminate the burden of quantifying qualitative concepts and model customer heterogeneity and design team's preference. Due to its easiness, our approach can reduce the cognitive burden of QFD planning team and give a practical convenience in QFD planning. Extensions to the proposed approach are also given to address application contexts involving a wider set of HOQ elements. (C) 2014 Elsevier B.V. All rights reserved.