Design of Alumina Reinforced Aluminium Alloy Composites with Improved Tribo-Mechanical Properties: A Machine Learning Approach

Artificial intelligence approach for data-driven design is employed to design an alumina reinforced aluminium matrix composite (AMC) with improved tribo-mechanical properties. Machine learning tool, viz. Artificial neural network (ANN), is used as a tool to create a set of models describing the properties of the AMC. The database required for the ANN modelling was extracted from published literature. The objective functions to search the optimum combinations of composition, size and morphological properties were provided from those ANN models. Since the objectives are conflicting in nature, a multi-objective optimization is introduced using genetic algorithm as a tool and the achieved Pareto solutions are used for designing the composite with tailored properties.