A Neutrosophic TOPSIS Framework for multi-criteria selection of Functionally Graded Materials

This research introduces a novel approach for the selection of Functionally Graded Materials (FGMs) using a modified TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method within a neutrosophic framework. FGMs represent an advanced class of composite materials with gradually varying properties across their dimensions, making their selection a complex multi-criteria decision-making problem. The neutrosophic set theory addresses uncertainty, imprecision, and indeterminacy inherent in expert evaluations and technical specifications. Our framework incorporates truth, indeterminacy, and falsity membership functions to represent decision parameters comprehensively. The methodology is validated through a case study involving the selection of FGMs for high-temperature aerospace applications, considering criteria such as thermal resistance, mechanical properties, manufacturing complexity, and cost-effectiveness. Results demonstrate that the proposed neutrosophic TOPSIS framework offers improved discrimination power and robustness compared to conventional TOPSIS and fuzzy TOPSIS methods. Sensitivity analysis confirms the stability of the ranking outcomes under varying criteria weights. This approach provides materials engineers and designers with a reliable decision support tool for selecting optimal FGM compositions tailored to specific application requirements.