An integrated design concept evaluation method based on best–worst entropy and generalized TODIM considering multiple factors of uncertainty

Abstract

Design concept evaluation (DCE) plays a vital role in the early design stage of new product development because it directly affects the direction of subsequent design and manufacturing activities. However, the previous DCE methods have some limitations, such as (i) they usually only consider one or two factors of uncertainty, while multiple factors of uncertainty are always involved in the group decision-making problems; (ii) the criteria weight calculations usually only consider the subjective expert experience or the objective statistical analysis, which is not complete; and (iii) the psychological behaviors of experts are ignored when considering gains or losses, all of which affect their precision. Hence, this study develops an integrated DCE model to address the above limitations. First, a new uncertain information manipulation method, namely interval-valued intuitionistic fuzzy rough clouds (IVIFRCs), is developed to handle the multiple factors of uncertainty in the group decision-making problems by integrating the interval-valued intuitionistic fuzzy sets (IVIFS)-based trapezium cloud model and the interval rough number (IRN) theory. Then, the arithmetic operations, distance measure, and aggregation operators for IVIFRCs are introduced and discussed. Furthermore, the best–worst and entropy methods are integrated as the best–worst entropy (BWE) to identify the hybrid criteria weights with IVIFRC information. Finally, the generalized TODIM (TOmada de Decisão Iterativa Multicritério) is applied to handle experts’ psychological behaviors as well as rank design concepts. Additionally, a case study, sensitivity analysis, and several comparisons are conducted. Results demonstrate that the developed model is superior to the existing DCE approaches.