A novel decision-making methodology for materials selection under uncertainty: modified fuzzy logic method

In this research work, a modified fuzzy approach referred to as modified fuzzy logic method (MFLM) is proposed to more conveniently solve intricate decision-making problems under uncertainty and data deficiency. The method resolves major drawbacks like inaccuracy, complexity, and a high volume of computational efforts with the existing approaches for the mentioned problems. Here, MFLM is applied to materials selection for a cryogenic storage tank and a gas turbine blade, which are standard engineering problems used for verification by researchers, and the ranking results are compared with the state-of-the-art techniques in the literature, such as the conventional fuzzy logic method. Spearman's rank correlation coefficient is used to measure the similarity between the offered rankings. The results show that MFLM, despite its simplicity, provides comparable outputs to the novel existing approaches. The average correlation between MFLM and considered techniques is about 90%, demonstrating a high level of agreement between rankings. MFLM offers SS 301-FH and CMSX-4 materials as the best alternatives for cryogenic storage tank and gas turbine blade examples, respectively. The mentioned materials are confirmed by both industry and other studied techniques and obtained by solving the problem in the fuzzy domain to incorporate uncertainties. Finally, a sensitivity analysis is performed to evaluate the robustness of the proposed method. MFLM indicates to be relatively insensitive to variations in criteria weightings.