Ranking optimization investigation using hybrid AHP-TOPSIS MCDM technique on hybrid AA2024 ― Ceramic particulate alloy composite materials prepared through stir casting

Abstract

Abstract In reality, most often have to make decisions such as ranking the finite available materials alternatives that meet certain performance norms/criteria fulfilling certain objectives/goals. The problem becomes more complex as the number of criteria and alternatives increases. In such scenarios, Multi-Criteria-Decision-Making (MCDM) techniques such as hybrid AHP (Analytical hierarchy process) – TOPSIS (Technique for Order Preferences by Similarity to Ideal Solution) and others assist in quantitative decision making by accounting for qualitative human judgments. For example, materials often used in sliding wear applications have numerous criteria for their performance, such as physical, mechanical, thermal, thermo-mechanical, etc. that controls/monitor their realistic sliding wear performance. Consequently, material scholars find it challenging to subjectively rank the composite materials compositions. Alternatively, MCDM techniques aid in quick material selection/ranking decision making. This research work illustrates the application of a hybrid AHP- TOPSIS technique to the ranking of alloy composites. The properties defining data such as physical, mechanical, thermal, thermo-mechanical, etc. are weighted using AHP technique, thereafter, relative weights are used to rank the alloy composite compositions by TOPSIS method. The compositions comprise of AA2024 alloy as matrix phase and reinforcing phase consists of silicon carbide, silicon nitride and graphite particulates. The ranking analysis orders are found to be consistent with subjective analysis. Furthermore, the robust ranking order was validated by sensitivity analysis.