Large-scale group decision-making for prioritizing engineering characteristics in quality function deployment under comparative linguistic environment

Abstract

Quality function deployment (QFD) is a well-known tool for quality management. With its systematic operation mechanism for translating customer requirements (CRs) into corresponding engineering characteristics (ECs), QFD highly facilitates product/service design and improvement. However, the evolution of the decision-making environment has made the quantification within the traditional QFD operation could hardly able to meet the demanded efficiency as well as the accuracy of the generated results. To cope with the problem, an enhanced large-scale group decision-making method that integrates proportional hesitant fuzzy linguistic term sets (PHFLTSs) and the cumulative prospect theory (CPT) is put forward by this study to determine the ranking priority of ECs in doing QFD. To facilitate QFD team members carry out an easier and more accurate evaluation, they would use comparative linguistic expressions in making judgments, and the comparative linguistic expressions are subsequently transformed into hesitant fuzzy linguistic term sets (HFLTSs). The obtained HFLTSs are transformed into PHFLTSs based on the statistical method under a group decision-making environment for preventing information loss, and, at the same time, improving calculation accuracy. Taking decision-makers’ heterogeneity and risk attitudes into consideration, the CPT method is adopted and extended under the PHFL environment to prioritize the ECs in QFD operation. To illustrate how the proposed large-scale group decision-making-based QFD method is to be applied, a case study about solar photovoltaic cell development is presented. Furthermore, a comparative analysis is conducted to exhibit the effectiveness of the proposed QFD method.