A Z-number and MABAC method based on reliability analysis and evaluation of product design concept

Abstract

Modular design is a significant method for complicated product development. In the context of modular design, involving users in concept assessment boosts a product's appeal but also introduces decision uncertainty and unreliability. As a solution, this paper proposed a hybrid method by integrating expert consensus modeling, attribute weighting, Z-number, and the Multi-Attribute Border Approximation Area Comparison (MABAC) method. Initially, a consensus model is established using consistency theory to determine expert weights, and attribute priorities are determined through the entropy weighting method. Subsequently, the Z-number-based MABAC method ranks the alternatives, determining the optimal solution among them. Using an automated outdoor cleaning vehicle as an example, the proposed method is compared to other techniques. The sensitivity analysis and the comparisons show that the proposed method improves the reliability and objective of the decision-making process.