In the present research work an effort has been made to study the wear and frictional behavior of Aluminium Metal Matrix composite (Al 7075 as a base alloy and y ash (FA) and silicon carbide (SiC) as reinforcements) by using the stir casting method. To carry out this work, the wt. % of reinforcements FA (2.5%, 5%, 7.5% and 10%) and SiC (2.5%, 5%, 7.5% and 10%)have been used 5%, 10%, 15% and 20%.Initially, the mechanical studies have been conducted and the best mechanical properties obtained at 20 wt. % of FA and SiC. Later on, the composite was fabricated by 20 wt. % of FA, SiC reinforcements are used to check the wear and frictional behavior on a pin-on-disc machine at the dry condition. The dry sliding wear behavior was carried out at various input parameters such as applied force (10N, 20N, and 30N), sliding velocity (1.5m/s, 3m/s, and 4.5m/s), and sliding distance (1000 m, 2000 m, and 3000 m).Further, a scanning electron microscope (SEM) are used to observe the mixing of reinforcements and examine the worn surfaces. A response surface methodology (RSM) is the reasonable and accurate method for conducting the experiments and identifying the optimal wear parameters. Moreover, the RSM was helped to identify the most signi cant factor, which was the in uence on the wear rate. Finally, it is decided that the applying force is the utmost signi cant factor that leaves an effect on wear rate. The sliding velocity and distance are acting as the lesser in uence on the performance indicator.

In the mechanical industries the tribological studies namely, wear rate (WR) and coefficient of friction (COF) are playing a significant role. Therefore, identifying the optimal parameters of wear and coefficient friction is a challenging task. To overcome this difficulty, in the present research work, the authors are using various non-traditional algorithms such as Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO) algorithms. The non-linear equation has been developed for T6-heat treated Al 7075/SiC/FA MMC’s using response surface methodology. The three independent factors such as sliding velocity (SV), applying load (AL), and sliding distance (SD) are used to optimize the WR and COF. Finally, the performances of the established algorithms are verified in terms of their capability to develop the optimum solution.

In the present research work an effort has been made to study the wear and frictional behavior of Aluminium Metal Matrix composite (Al 7075 as a base alloy and fly ash (FA) and silicon carbide (SiC) as reinforcements) by using the stir casting method. To carry out this work, the wt. % of reinforcements FA (2.5%, 5%, 7.5% and 10%) and SiC (2.5%, 5%, 7.5% and 10%)have been used 5%, 10%, 15% and 20%. Initially, the mechanical studies have been conducted and the best mechanical properties obtained at 20 wt. % of FA and SiC. Later on, the composite was fabricated by 20 wt. % of FA, SiC reinforcements are used to check the wear and frictional behavior on a pin-on-disc machine at the dry condition. The dry sliding wear behavior was carried out at various input parameters such as applied force (10N, 20N, and 30N), sliding velocity (1.5m/s, 3m/s, and 4.5m/s), and sliding distance (1000 m, 2000 m, and 3000 m). Further, a scanning electron microscope (SEM) are used to observe the mixing of reinforcements and examine the worn surfaces. A response surface methodology (RSM) is the reasonable and accurate method for conducting the experiments and identifying the optimal wear parameters. Moreover, the RSM was helped to identify the most significant factor, which was the influence on the wear rate. Finally, it is decided that the applying force is the utmost significant factor that leaves an effect on wear rate. The sliding velocity and distance are acting as the lesser influence on the performance indicator.

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