An improved interval‐grey‐probability QFD method for prioritizing engineering characteristics under vague environment

Abstract

At present, the interval‐grey quality function deployment (QFD) has been widely used to address a vague information at the early stage of product design. However, the existing interval‐grey QFD method suffers from a problem that it is incapable of comparing specific values from any two intervals within overlapping segments associated with the importance of engineering characteristics (ECs) during the process of prioritizing their importance. This problem consequently impedes the effective prioritization of their magnitudes, thus hindering the prioritization of the importance of ECs. Aiming at addressing the problem, an improved interval‐grey‐probability QFD method is proposed. The proposed method integrates interval grey numbers, grey relational analysis (GRA), and interval‐probability ranking method into the interval‐grey QFD framework to prioritize the importance of ECs under a vague environment. Specifically, the interval grey numbers are used to assess the importance of customer requirements (CRs) and the GRA method is adopted to construct the relationship matrix of CRs‐ECs, respectively. Based on the importance of CRs and the relationship matrix of CRs‐ECs, the interval‐probability ranking method is introduced to measure the prioritization of the importance of ECs. The proposed method is validated by a multi‐function flash drive. Results show that the proposed method is more accurate than existing methods in terms of the deviation degree.