Abstract
Quality function deployment (QFD) is an effective approach to satisfy the customer requirements (CRs). Furthermore, accurately prioritizing the engineering characteristics (ECs) as the core of QFD is considered as a group decision making (GDM) problem. In order to availably deal with various preferences and the vague information of different experts on a QFD team, multi-granularity 2-tuple linguistic representation is applied to elucidate the relationship and correlation between CRs and ECs without loss of information. In addition, the importance of CRs is determined using the best worst method (BWM), which is more applicable and has good consistency. Furthermore, we propose considering the relationship matrix and correlation matrix method to prioritize ECs. Finally, an example about evaluating emergency routes of metro station is proposed to illustrate the validity of the proposed methodology.
Highlights
In order to cope with intense global competitions, enterprises must design the highest quality products that satisfy the voice of customers (VOCs)
A four-phase Quality function deployment (QFD) model is employed to translate the VOCs to engineering characteristics (ECs), which consists of Product
In view of the Bonferroni mean (BM) operator capturing the interrelationship between input information and ranking ECs under a 2-tuple environment, so the 2-tuple linguistic weighted geometric Bonferroni mean (2TLWGBM) operator [33] will be applied to prioritize the sequence of ECs
Summary
In order to cope with intense global competitions, enterprises must design the highest quality products that satisfy the voice of customers (VOCs). Fuzzy multiple objective programming [7], fuzzy goal programming [8], fuzzy relationship and correlations [9], and expected value-based method [10] are proposed to prioritize ECs. In addition, Geng et al [11] integrated the analytic network process to QFD to reflect the initial importance weights of ECs. the problem is that they paid little attention to the GDM method, which can aggregate different experts’. In order to fill the gap, it is necessary that the QFD methodology is extended with a 2-tuple linguistic environment so as to lessen the loss of information and obtain accurate value of ECs. In addition, decision makers may have different knowledge and experience in the process of group decision making, and they may adopt different linguistic labels to describe the same decision-making problems.
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