Improving quality function deployment analysis with the cloud MULTIMOORA method

Quality function deployment (QFD) is a quality guarantee method extensively used in various industries, which can help enterprises shorten the product design period and enhance the manufacturing and managing work. The task of selecting important engineering characteristics (ECs) in QFD is crucial and often involves multiple customer requirements (CRs). In this paper, a modified multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method based on cloud model theory (called C-MULTIMOORA) is developed to determine the ranking order of ECs in QFD. First, the linguistic assessments provided by decision makers are transformed into normal clouds and aggregated by the cloud weighted averaging operator. Then, the weights of CRs are determined based on a maximizing deviation method with incomplete weight information. Finally, the importance of ECs is obtained using the C-MULTIMOORA method. An empirical case conducted in an electric vehicle manufacturing organization is provided together with a comparative analysis to validate the advantages of our proposed QFD model.