Graphene/Al6061 nanocomposite selection using TOPSIS and EXPROM2 multi-criteria decision-making methods

Abstract

Inventions of novel nanocomposites are highly recommended due to predominant physical, mechanical characteristics and infinite design possibilities. Manufacturing of these nanocomposites is a costly and challenging task, as it can show unpredictable characteristics behavior and different order of importance considered prior to manufacturing. Therefore, the selection of the most suitable nanocomposite fulfilling characteristics requirement in specific applications is highly needed. To tackle this difficulty, a novel approach to use multicriteria decision-making (MCDM) models to the nanocomposite selection was presented in this research. The TOPSIS (technique of order preference similarity to the ideal solution) and extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment of evaluations) multicriteria decision models were used for the best alternative selection of novel graphene/Al6061 nanocomposites. The graphene/Al6061 nanocomposites were fabricated and characterized to tackle the low strength and hardness deficiency of Al6061. The criteria weights were determined by AHP (analytical hierarchy process). All nanocomposites were ranked and results were compared. The best materials were found as 10G (10% graphene reinforcement) due to excellent ultimate tensile strength (279.69 MPa), hardness (93.73 BHN), proof stress (248.55 MPa), though material cost (506.81 Rs) is high. The results of MCDM analysis were found satisfactory and can be utilized in design and manufacturing in aerospace, automobile, transportation, defense, and other applications.