New approach for quality function deployment based on social network analysis and interval 2-tuple Pythagorean fuzzy linguistic information

Abstract

Quality function deployment (QFD) is a useful quality management tool for the transformation of customer requirements (CRs) into engineering characteristics (ECs) in product development. In the literature, a lot of QFD approaches have been proposed to overcome the deficiencies and enhance the performance of the traditional QFD method. However, there are several issues deserving further investigation for improving QFD: majority of the existing methods describe experts’ opinions with single linguistic terms directly, which may produce the loss of information; most of the improved QFD methods cannot take the consensus levels among experts into account. In this study, we develop a new integrated QFD approach based on the interval 2-tuple Pythagorean fuzzy linguistic sets (I2PFLSs), the social network consensus reaching (SNCR) model, and an extended combined compromise solution (CoCoSo) method. There are three main contributions of the presented study: First, the correlation assessments between CRs and ECs given by experts are handled with the I2PFLSs. Second, the SNCR with minimum adjustment distance is employed to coordinate experts’ conflict correlation assessments by considering their trust relationships. Third, an extended CoCoSo method is employed to determine the importance ranking of ECs within the interval 2-tuple Pythagorean fuzzy linguistic environment. Finally, we present an electric vehicle product development case to demonstrate the effectiveness and superiority of the proposed QFD approach. The results show that the new QFD can express experts’ fuzzy and uncertain linguistic assessment information flexibly, deal with experts’ consensus in correlation assessment process, and yield more precise importance ranking of ECs for product improvement.