Zheng, P, Xu, X and Xie, SQ (2019) A weighted interval rough number based method to determine relative importance ratings of customer requirements in QFD product planning. Journal of Intelligent Manufacturing, 30 (1). pp. 3-16. ISSN 0956-5515
Abstract
Customer requirements (CRs) play a significant role in the product development process, especially in the early design stage. Quality function deployment (QFD), as a useful tool in customer-oriented product development, provides a systematic approach towards satisfying CRs. Customers are heterogeneous and their requirements are often vague, therefore, how to determine the relative importance ratings (RIRs) of CRs and eventually evaluate the final importance ratings is a critical step in the QFD product planning process. Aiming to improve the existing approaches by interpreting various CR preferences more objectively and accurately, this paper proposes a weighted interval rough number method. CRs are rated with interval numbers, rather than a crisp number, which is more flexible to adapt in real life; also, the fusion of customer heterogeneity is addressed by assigning different weights to customers based on several factors. The consistency of RIRs is maintained by the proposed procedures with design rules. A comparative study among fuzzy weighted average method, rough number method and the proposed method is conducted at last. The result shows that the proposed method is more suitable in determining the RIRs of CRs with vague information.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Science+Business Media New York 2016. This is an author produced version of a paper published in Journal of Intelligent Manufacturing. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/s10845-016-1224-z. |
Keywords: | Quality function deployment; Rough set theory; Fuzzy set theory; Product planning; Customer-centric design |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Mar 2017 11:15 |
Last Modified: | 30 Jan 2019 14:25 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/s10845-016-1224-z |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:113392 |