Investigation of Dry Sliding Tribological Behaviour of Epoxy Composites Filled with Hemp Particulates Using Artificial Neural Networks.

To address the need for wear-impenetrable packaging in shipment and related sectors, a treated hemp filler-reinforced epoxy composite manufactured in-house is subjected to tribological testing to assess its utilization under extensional load. The surface modification approaches are utilized on hemp fibres by employing alkali treatment with sodium hydroxide solution. Wear tests are executed on the developed samples in a dry atmosphere employing a pin-on-disc (POD) tribometer for three variable applied forces (5, 10, and 15 N), a sliding velocity of 550 RPM, and three sliding lengths (1000, 2000, and 3000 m) for friction against a stainless-steel disc. The mechanical properties (density, tensile, and flexural) of the composites are also assessed. The results indicated the effects of operating parameters and filler percentage in the test samples. Among all composites, 2.5 and 7.5 wt% hemp filler composite has generated the minimum wear and better mechanical characterization. Employing scanning electron microscope, the physical characterization of composites is carried out where fractures, debonding and deformation on the surfaces are seen. Apart from the tests, the wear properties of the composites with varying filler percentages are also predicted using artificial neural network (ANN) models. [ABSTRACT FROM AUTHOR]