Optimization of wear and frictional parameters using IWO and PSO algorithms

Abstract

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.