An evidential reasoning based approach for quality function deployment under uncertainty

被引:60
|
作者
Chin, Kwai-Sang [1 ]
Wang, Ying-Ming [2 ]
Yang, Jian-Bo [3 ]
Poon, Ka Kwai Gary [1 ]
机构
[1] City Univ Hong Kong, Dept Mfg Engn & Engn Management, Kowloon Tong, Hong Kong, Peoples R China
[2] Fuzhou Univ, Sch Publ Adm, Fuzhou 350002, Peoples R China
[3] Univ Manchester, Manchester Business Sch, Manchester M13 9PL, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
Quality function deployment; Group decision making; Uncertainty modeling; Evidential reasoning; Preference programming; PRIORITIZE DESIGN REQUIREMENTS; MULTIATTRIBUTE DECISION-ANALYSIS; CUSTOMER REQUIREMENTS; IMPORTANCE WEIGHTS; ENGINEERING CHARACTERISTICS; MAKING APPROACH; FUZZY QFD; MODEL; AHP; FRAMEWORK;
D O I
10.1016/j.eswa.2008.06.104
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Quality function deployment (QFD) is a methodology for translating customer wants (WHATs) into relevant engineering design requirements (HOWs) and often involves a group of cross-functional team members from marketing, design, quality, finance and production and a group of customers. The QFD team is responsible for assessing the relationships between WHATs and HOWs and the interrelationships between HOWs, and the customers are chosen for assessing the relative importance of each customer Each member and customer from different backgrounds often demonstrates significantly different want. behavior from the others and generates different assessment results, complete and incomplete, precise and imprecise, known and unknown, leading to the QFD with great uncertainty. In this paper, we present an evidential reasoning (ER) based methodology for synthesizing various types of assessment information provided by a group of customers and multiple QFD team members. The proposed ER-based QFD methodology can be used to help the QFD team prioritize design requirements with both customer wants and customers' preferences taken into account. It is verified and illustrated with a numerical example. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:5684 / 5694
页数:11
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