Selecting the right matrix material is an important part of designing aluminum-based composite systems that is often forgotten. It has a big effect on how well the system works, how easy it is to make, and how much it costs. Most current research focuses on the selection of reinforcements or processing routes, rendering the choice of matrix predominantly intuitive or data-driven. This study suggests a structured and experimentally supported way to choose matrix materials using an integrated Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach. Five primary criteria—tensile strength, hardness, melting point, density, and cost—were utilized to assess prospective 7XXX-series aluminum alloys. We used fuzzy AHP to find the weights of the criteria, and then we used TOPSIS to rank the options. To confirm the decision-making result, hybrid aluminum metal matrix composites were created using the selected alloys under the same processing and reinforcement conditions. The composites were characterized experimentally by measuring their density, hardness, and tensile strength. These measurements were then used to determine the final ranking. The results consistently identified AA7075 as the best matrix material, showing that the proposed framework for designing aluminum hybrid MMCs is strong and useful in real life.
Buch et al. (Tue,) studied this question.