A group multi-granularity linguistic-based methodology for prioritizing engineering characteristics under uncertainties. (January 2016)

• Record Type: Journal Article
• Authors: Wang, Zengqiang; Fung, Richard Y.K.; Li, Yan-Lai; Pu, Yun
• Is Part Of: Computers & industrial engineering. Volume 91(2016)
• Page Start: 178
• Page End: 187
• Publication Date: 2016-01
• Subjects: Quality function deployment -- House of quality -- Customer requirements -- Engineering characteristics -- Unbalanced linguistic label set -- Group decision making; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2015.11.012
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A framework illustrating the requirement to prioritize ECs is presented. Multiple linguistic sets are used to express decision-makers' preferences. Both positive and negative associations between CRs and ECs are considered. Abstract: Quality Function Deployment (QFD) is a customer driven tool for product development. Prioritizing Engineering Characteristics (ECs) is a crucial stage in QFD. However, the complex and imprecise factors in QFD present many difficulties for the analysis process of ranking ECs. Even though different techniques have been applied to determine the importance of ECs, they do not fully express all the preferences involved, which could affect the preciseness of results. To address the vague information at the early stage of product development effectively, this paper presents a group multi-granular linguistic-based approach to enable customers or developers to express their preferences using different linguistic label sets. Using different linguistic label sets although makes the process more complicated, it is more meaningful and more practical. Apparently, the proposed method may not only reflect the vague information effectively, but also avoid the risk of information loss. The proposed approach uses a two-phase framework to determine the priority of CRs and evaluate the priority of ECs. A case example is given to illustrate the feasibility and validity of the proposed method. The proposed approach is superior to the existing approach in terms of robustness.