Wear analysis of waste marble dust-filled polymer composites with an integrated approach based on design of experiments and neural computation

Abstract

Waste marble dust is a solid waste generated during the cutting and polishing of marble pieces in construction sites and also in marble processing industries. This paper reports on the utilization of this waste as a filler material in particulate-filled polymer composite. Polyester-based composites are prepared with different weight proportions of waste marble dust and the dry sliding wear behavior of these composites is studied. Wear trials are conducted using a pin-on-disc test apparatus based on the Taguchi’s L25 orthogonal array as per ASTM G 99-05. The effects of different parameters on the specific wear rate of the composites are studied and an optimum combination of parameters is obtained for the least wear rate. Based on the experimental data, a prediction model using the artificial neural network is used to predict the specific wear rate of the composites at a wider range of operating parameters, within and beyond the test region. The morphologies of the worn surfaces are studied by a scanning electron microscope to ascertain the wear mechanism of the composites at different conditions. This work thus opens up a new avenue for the value added utilization of a waste like marble dust in tribological applications.