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research-article

An improved grey quality function deployment approach using the grey TRIZ technique

Authors:

Hung-Sheng ChengAuthors Info & Claims

Computers and Industrial Engineering, Volume 92, Issue C

Pages 57 - 71

https://doi.org/10.1016/j.cie.2015.11.003

Published: 01 February 2016 Publication History

Abstract

We develop an improved grey QFD method by integrating interval grey numbers, QFD and TRIZ techniques.The proposed TRIZ method can effectively resolve contradiction problems between conflicting EC pairs.The input values and output results of the proposed method are interval grey numbers.A new grey ranking method is designed to precisely rate interval grey numbers. Quality function deployment (QFD) can simultaneously consider both product functions and consumer needs during the product design and manufacturing stages. Traditional QFD often relies on market research or customer questionnaires to collect customer opinions in order to establish customer requirements. However, market research results (or those of customer questionnaires) usually contain a good deal of uncertain and incomplete information. Moreover, there is a practical problem in implementing QFD as experts in specific fields are often rare and difficult to find. In order to resolve these issues, this study integrated interval grey numbers, QFD and TRIZ techniques to develop an improved grey quality function deployment (GQFD) method. GQFD can assist product developers in identifying important engineering characteristics and can provide suggestions for possible improvements in engineering characteristics. Furthermore, this study developed a new grey ranking method to determine the ranking order of interval grey numbers. Finally, a real-world case study in Taiwan was used to explain the research process of the GQFD method and validate the practicality of the proposed method.

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Cited By

Guo HDeng S(2025)Condition Identification of Calcining Kiln Based on Fusion Machine Learning and Semantic WebInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.36520321:1(1-36)Online publication date: 3-Jan-2025
https://dl.acm.org/doi/10.4018/IJSWIS.365203
Wang JYu LRong Y(2024)A new CoCoSo ranking-based QFD approach in Pythagorean fuzzy environment and its application on evaluating design attributes of mobile medical AppJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23322946:2(3677-3700)Online publication date: 14-Feb-2024
https://dl.acm.org/doi/10.3233/JIFS-233229
Geng XLi YZhang HHe J(2023)Configuration optimization of product-service system design requirements based on hesitant information axiomJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23132945:5(9007-9028)Online publication date: 4-Nov-2023
https://dl.acm.org/doi/10.3233/JIFS-231329
Show More Cited By

An improved grey quality function deployment approach using the grey TRIZ technique
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Published In

cover image Computers and Industrial Engineering

Computers and Industrial Engineering Volume 92, Issue C

February 2016

116 pages

ISSN:0360-8352

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 February 2016

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Cited By

Guo HDeng S(2025)Condition Identification of Calcining Kiln Based on Fusion Machine Learning and Semantic WebInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.36520321:1(1-36)Online publication date: 3-Jan-2025
https://dl.acm.org/doi/10.4018/IJSWIS.365203
Wang JYu LRong Y(2024)A new CoCoSo ranking-based QFD approach in Pythagorean fuzzy environment and its application on evaluating design attributes of mobile medical AppJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23322946:2(3677-3700)Online publication date: 14-Feb-2024
https://dl.acm.org/doi/10.3233/JIFS-233229
Geng XLi YZhang HHe J(2023)Configuration optimization of product-service system design requirements based on hesitant information axiomJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23132945:5(9007-9028)Online publication date: 4-Nov-2023
https://dl.acm.org/doi/10.3233/JIFS-231329
Xiao JWang XZhang H(2022)Coping with diversity ratings in prioritizing design requirements in quality function deploymentComputers and Industrial Engineering10.1016/j.cie.2021.107799163:COnline publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1016/j.cie.2021.107799
Yang WCao GPeng QSun Y(2021)Effective radical innovations using integrated QFD and TRIZComputers and Industrial Engineering10.1016/j.cie.2021.107716162:COnline publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.cie.2021.107716
Aguilar-Lasserre ATorres-Sánchez VFernández-Lambert GAzzaro-Pantel CCortes-Robles GRomán-del Valle M(2020)Functional optimization of a Persian lime packing using TRIZ and multi-objective genetic algorithmsComputers and Industrial Engineering10.1016/j.cie.2018.12.005139:COnline publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1016/j.cie.2018.12.005
Eshghi AMousavi SMohagheghi V(2019)A new interval type-2 fuzzy approach for analyzing and monitoring the performance of megaprojects based on earned value analysis (with a case study)Neural Computing and Applications10.1007/s00521-018-04002-x31:9(5109-5133)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s00521-018-04002-x

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