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Quantification and integration of an improved Kano model into QFD based on multi-population adaptive genetic algorithm

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Quantification and integration of an improved Kano model into QFD based on multi-population adaptive genetic algorithm

作者:He, LN(He, Lina);Song, WY(Song, Wenyan);Wu, ZY(Wu, Zhenyong);Xu, ZT(Xu, Zhitao);Zheng, MK(Zheng, Maokuan);Ming, XG(Ming, Xinguo)

COMPUTERS & INDUSTRIAL ENGINEERING

卷:114

页:183-194

DOI:10.1016/j.cie.2017.10.009

出版年:DEC 2017

摘要

In an effort to address the inherent deficiencies of traditional Kano model and quality function deployment (QFD), this paper proposes an improved Kano model named as importance-frequency Kano (IF-Kano) model and integrates IF-Kano model into QFD. Considering the interaction between frequencies and importance weights of customer requirements (CRs), the IF-Kano model adopts the logical Kano classification criteria to categorize CRs. Then, both qualitative and quantitative results derived from IF-Kano model are integrated into QFD with a non-linear programming model. The model aims to determine appropriate Kano categories of CRs and target values of engineering characteristics (ECs) with a view to achieving an optimal design solution under the best balance between enterprise satisfaction and customer satisfaction (CS). To solve the presented model, a multi-population adaptive genetic algorithm (MPAGA) is designed. Finally, an example of a home elevator design is given to demonstrate the feasibility and effectiveness of the developed approach and algorithm.

关键词

作者关键词:Kano model;Quality function development;Customer requirement;Multi-population adaptive genetic algorithm

KeyWords Plus:QUALITY FUNCTION DEPLOYMENT;MODIFIED EVEN-SWAPS;CUSTOMER SATISFACTION;PRODUCT DEVELOPMENT;ISSUE NEGOTIATION;PROGRAMMING-MODEL;DECISION-MAKING;DESIGN;REQUIREMENTS;METHODOLOGY

作者信息

通讯作者地址:He, LN (通讯作者)

地址:

电子邮件地址:he20051049@126.com

出版商

PERGAMON-ELSEVIER SCIENCE LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND

类别 / 分类

研究方向:Computer Science; Engineering

Web of Science 类别:Computer Science, Interdisciplinary Applications; Engineering, Industrial

文献信息

文献类型:Article

语种:English

入藏号:WOS:000418314300016

ISSN:0360-8352

eISSN:1879-0550

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