An Optimization Approach to the Dry Sliding Wear Behavior of Particulate Filled Glass Fiber Reinforced Hybrid Composites

The new set of hybrid composites consisting of randomly oriented short e glass fiber reinforcement, polyester resin and titanium oxide (TiO2) particulate were developed by hand layup technique. Wear test was carried out by rubber wheel abrasive test (RWAT) rig with the four operating variables filler content, applied load, abrasive grit size (Al2O3) and test duration. The wear test of the composites were done on the basis of Taguchi's L9 (34) Orthogonal array. Analysis of variance and S/N ratio was used to study the optimum wear. From, Taguchi's experimental design a mathematical regression model of the wear rate was suggested. Genetic algorithm (GA) was used to compare the result which obtained from Taguchi's design of experiment. The fitness graph from the GA gives the better fitness function in which the operating variables were determined and the minimum wear rate was obtained. Scanning Electron Microscopy (SEM) image discovered to review the crater formation and fiber pull out.