Characterization, Prediction, and Optimization of Dry Sliding Wear Behaviour of Al6061/WC Composites

Abstract

This investigation deals with an experimental analysis done on dry sliding wear behaviour of aluminium matrix composites reinforced with WC (tungsten carbide) particles. The composites were processed through powder metallurgy (P/M) technique with the addition of various fractions of WC particles. Results of scanning electron microscope (SEM) examinations and XRD analysis showed better dispersion of the reinforced particles and good matrix–reinforcement interface integrity. The results of dry sliding wear tests conducted on composite samples were analysed for varied conditions of WC volume fraction and sliding distance. The wear properties of composites were significantly affected by the variation of the WC volume percentage (5–25%). Smother wear tracks and closely spaced grooves on the composite pin worn surfaces were found for higher volume fraction WC particles. The postulated regression models for prediction of wear behaviour approximate their experimental values with an estimated error from 1.97 to 6.56%. The derived optimal wear properties to improve the sliding wear performance of the composites through a novel hybrid (GRA integrated TLBO) multi-response optimization approach are in a closer correlation with the experimentally measured values. Also, wear performance predicted values through hybrid multi-response optimization are closer to their validation experimental results compared with the predicted values through TLBO and GRA approaches. The derived optimal set of wear properties are 1.921 mm3/m wear rate and 0.292 coefficient of friction at 15 vol% of WC, 10 N applied load, 775 m sliding distance, and 1 m/s sliding velocity. The surfaces of the composite samples tested at the derived set of optimal wear behavioural parameters were also examined through SEM and analysed.