New approach for quality function deployment based on proportional hesitant fuzzy linguistic term sets and prospect theory

As a powerful instrument to fulfil customer needs, quality function deployment (QFD) is capable of converting customer requirements (CRs) into appropriate engineering characteristics (ECs) in the product design and development. Nevertheless, the inherent defects of the conventional QFD, such as the description of experts' opinions with crisp numbers and the non-robust ranking of ECs, confine its efficiency and potential applications. In this study, a novel QFD approach using proportional hesitant fuzzy linguistic term sets (PHFLTSs) and prospect theory is proposed to overcome the insufficiencies of the traditional QFD. Specifically, the relationships between CRs and ECs are represented by PHFLTSs and the weights of CRs are derived with the best-worst method (BWM). An extended prospect theory is employed for the prioritisation of the ECs that have been identified. Finally, two application examples are provided to examine the applicability and advantages of our proposed QFD approach.