Parametric Analysis for Erosion Wear of Waste Marble Dust-Filled Polyester Using Response Surface Method and Neural Networks

Abstract

In this research, the erosion wear characterization of waste marble dust (an industrial/construction waste)-filled polyester composites is evaluated. The relative effect of the control factors on the erosion rate of the composites is experimentally and statistically evaluated using a statistical model based on the response surface method, and the mechanisms of erosion loss are studied from the worn surface morphologies taken using a scanning electron microscope. The analysis reveals that striking velocity, filler concentration, and impingement angle in that sequence are the significant control factors affecting the erosion rate of the composites. The erosion efficiency of the composites is calculated to ascertain the erosion behavior of the composites. Further, an analytical as well as predictive model working on neural networks, is used to predict the erosion rate of the composites at different levels of the individual control factors. Such composites are expected to be advantageous in wear-related applications.