Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Pages (from-to) | 3583-3604 |
Journal / Publication | International Journal of Production Research |
Volume | 43 |
Issue number | 17 |
Publication status | Published - 1 Sept 2005 |
Link(s)
Abstract
Quality function deployment (QFD) is a planning and problem-solving tool that is renowned for translating customer requirements into the technical attributes of a product. To deal with the imprecise elements in the development process, fuzzy set theory is incorporated into QFD methodology. A novel fuzzy expected value operator approach is proposed in this paper to model the QFD process in a fuzzy environment, and two fuzzy expected value models are established to determine the target values of engineering characteristics in handling different practical design scenarios. Analogous to stochastic programming, the underlying philosophy in the proposed approach is based on selecting the decision with maximum expected returns. Furthermore, the proposed approach considers not only the inherent fuzziness in the relationships between customer requirements and engineering characteristics, but also the correlation among engineering characteristics. These two kinds of fuzzy relationships are aggregated to give the fuzzy importance of individual engineering characteristics. Finally, an example of a quality improvement problem of a motor car design is given to demonstrate the application and performance of the proposed modelling approach. © 2005 Taylor & Francis Group Ltd.
Research Area(s)
- Customer requirements, Engineering characteristics, Fuzzy expected value operator, Product design, Quality function deployment, Targets setting
Citation Format(s)
Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD. / Chen, Y.; Fung, R. Y K; Tang, J.
In: International Journal of Production Research, Vol. 43, No. 17, 01.09.2005, p. 3583-3604.
In: International Journal of Production Research, Vol. 43, No. 17, 01.09.2005, p. 3583-3604.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review