TY - JOUR
T1 - A New Method for Quality Function Deployment Based on Rough Cloud Model Theory
AU - Fang, Hong
AU - Li, Jing
AU - Song, Wenyan
N1 - Publisher Copyright:
© 1988-2012 IEEE.
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Quality function deployment (QFD) has been a popular product or service development method to convert customer needs (CNs) into technical requirements (TRs). Nevertheless, the traditional QFD has vagueness inherent in experts' opinions in determining CNs' weights and the relationship between CNs and TRs. In the previous research works, fuzzy set theory is popular to deal with imprecise information in QFD. However, it still suffers from several deficiencies. For example, it needs prior information that leads to relatively fixed intervals expressing vagueness; and it assumes the membership degrees are crisp. To solve the issues, this article develops an integrated QFD method, where rough sets and cloud model are utilized for treating uncertain information. The former expresses impreciseness without any other assumptions and the latter considers expert evaluations' randomness. In order to obtain more comprehensive importance of CNs, a combination weighting method is utilized. In the end, a compressor rotor's industrial service design is conducted utilizing the proposed method, where its effectiveness is verified.
AB - Quality function deployment (QFD) has been a popular product or service development method to convert customer needs (CNs) into technical requirements (TRs). Nevertheless, the traditional QFD has vagueness inherent in experts' opinions in determining CNs' weights and the relationship between CNs and TRs. In the previous research works, fuzzy set theory is popular to deal with imprecise information in QFD. However, it still suffers from several deficiencies. For example, it needs prior information that leads to relatively fixed intervals expressing vagueness; and it assumes the membership degrees are crisp. To solve the issues, this article develops an integrated QFD method, where rough sets and cloud model are utilized for treating uncertain information. The former expresses impreciseness without any other assumptions and the latter considers expert evaluations' randomness. In order to obtain more comprehensive importance of CNs, a combination weighting method is utilized. In the end, a compressor rotor's industrial service design is conducted utilizing the proposed method, where its effectiveness is verified.
KW - Cloud model theory
KW - combination weighting method
KW - quality function deployment
KW - rough set philosophy
UR - https://www.scopus.com/pages/publications/85091311790
U2 - 10.1109/TEM.2020.3020339
DO - 10.1109/TEM.2020.3020339
M3 - 文章
AN - SCOPUS:85091311790
SN - 0018-9391
VL - 69
SP - 2842
EP - 2856
JO - IEEE Transactions on Engineering Management
JF - IEEE Transactions on Engineering Management
IS - 6
ER -