Optimization of Tribological Properties of Al6061/9%Gr/WC Hybrid Metal Matrix Composites Using FGRA

Abstract

In the present work, Hybrid MMCs are developed using Al6061 as a matrix with graphite (Gr) and tungsten carbide (WC) as reinforcements. This investigation is motivated to estimate the tribological properties such as wear phenomenon and coefficient of friction. The composites produced through stir casting route, initially 3, 6, 9, and 12% of Gr are produced and the investigation of these composites for mechanical and microstructural properties indicates that 9% Gr shows better performance. So, hybrid composite of Al6061/9%Gr/WC (WC varies from 1, 2, 3%) produced. Thereafter in view of modeling and optimization of the tribological property of the composites, the wear tests are conducted on pin-on-disk tribometer under varying conditions of reinforcement percentage, load, sliding distance, and sliding velocity according to face-centered central composite design that consists of 30 experimental runs. The wear rate and coefficient of friction are recorded as the tribological property indicators. Regression models for each response in terms their control variables were developed and checked their adequacy with ANOVA. Consequently, these models were used for optimization. Fuzzy gray relational analysis (FGRA) was used to derive the values of optimal control variable. The suitability of this multi-response optimization approach which minimizes the wear rate and coefficient of friction simultaneously was analyzed and reported. Finally, the derived optimal tribological conditions of the composites were confirmed through the validation experimental results.