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Journal of Intelligent Manufacturing

, Volume 30, Issue 5, pp 2231–2243 | Cite as

User selection for collaboration in product development based on QFD and DEA approach

  • Xuefeng ZhangEmail author
Article

Abstract

User collaboration has been recognized as a critical factor in successful product development. To select the proper users who have a higher satisfaction to meet product development requirements, this study proposes an integrated approach based on quality function deployment (QFD) and data envelopment analysis (DEA). The proposed approach considers product development requirements, the inner dependencies of user evaluation criteria, and the relationships between requirements and criteria simultaneously and presents them in house of quality (HoQ). For the fuzzy and imprecise information in HoQ, fuzzy weighted average method is employed to determine the weight of each user evaluation criterion. Furthermore, to determine the priorities of users with a large number efficiently, this study implements linguistic variables to assess the weight of each user under each criterion, the DEA method to determine the optimal values of linguistic variables, and the simple additive weighting approach to aggregate the weight of each criteria and the local score of each user with respect to each criterion. An illustrative case is presented to demonstrate the applications of the proposed approach based on QFD and DEA in this paper.

Keywords

User selection Collaborative product development Quality function deployment Multiple-criteria decision making Data envelopment analysis 

Notes

Acknowledgements

This work was supported by The Key Project of Academic Humanities and Social Science of Anhui Education Department (SK2017A0120), and The Scientific Research Starting Foundation of Anhui Polytechnic University for Talent Introduction (2016YQQ008). The author would like to thank the anonymous reviewers and the editor for their constructive comments and suggestions.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Industrial Engineering, School of Management EngineeringAnHui Polytechnic UniversityWuhuChina

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