Consensus-driven methodology to managing diversity and complex linguistic ratings in quality function deployment: An optimization-based approach

Abstract

Quality function deployment (QFD) is a quality management tool that can effectively transform customer requirements (CRs) into engineering characteristics (ECs) of services or products. It is a crucial process to determine the prioritization of ECs from the assessments of the relationship between CRs and ECs in QFD. This study designs several optimization models to derive the consensual prioritization of ECs from the diverse and complex assessments, in which the assessments of QFD team members are modelled by comparative linguistic expressions (CLEs). First, a consensus-driven optimization model (CDOM) is presented to manage CLEs by transforming them into linguistic distribution assessments. Then, a minimum adjustment element consensus model (MAECM) is developed to derive the consensual assessments by minimizing the number of adjustment elements between the members’ original and adjusted assessments. Following this, a technique for order preference by the similarity to ideal solution (TOPSIS) based method is used to derive the prioritization of ECs from the consensual assessments. A case study regarding the improvement of window services in the Bank of JT Shanghai Branch is proposed to illustrate the implementation of the presented method. The comparative analysis shows that the presented method outperforms previous methods in managing CLEs and consensus.