An ordinal scale-based GDM approach to prioritize customer requirements in QFD product planning
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) | 4349-4367 |
Journal / Publication | Journal of Intelligent and Fuzzy Systems |
Volume | 37 |
Issue number | 3 |
Publication status | Published - 9 Oct 2019 |
Link(s)
Abstract
Quality function deployment (QFD) is an effective tool for the design and improvement of products/services. The prioritization of customer requirements (CRs), as an essential component of the house of quality, is fundamental and strategic in the whole process of QFD product planning. This study proposes a novel ordinal scale values based group decision-making (GDM) approach first and it is subsequently used to prioritize CRs in QFD product planning. The proposed approach is composed of three stages, that is, constructing the integrated preference vector, defining the extraction sequence and constructing the comprehensive preference vector. The proposed GDM approach is good for utilizing the ordinal scale values provided by respondents due to limited experience and knowledge. An illustrative example is presented to verify the applicability and efficiency of the proposed approach. Further, to demonstrate the superiority of the proposed approach, comparisons are made between the proposed approach and two other similar methods. Practical results demonstrated that the proposed approach can be effective when the importance of customers and the preference evaluations of CRs are given by an ordinal scale.
Research Area(s)
- customer requirement (CR), group decision-making (GDM), ordinal scale, preference ordering, Quality function deployment (QFD)
Citation Format(s)
An ordinal scale-based GDM approach to prioritize customer requirements in QFD product planning. / Yang, Qiang; Li, Yan-Lai; Chin, Kwai-Sang.
In: Journal of Intelligent and Fuzzy Systems, Vol. 37, No. 3, 09.10.2019, p. 4349-4367.
In: Journal of Intelligent and Fuzzy Systems, Vol. 37, No. 3, 09.10.2019, p. 4349-4367.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review