In this investigation, an attempt to predict the wear behaviour of hybrid metal matrix composites (MMCs) was carried out using artificial neural network (ANN) as well as the design of experiment (DoE) approaches. The investigated composite alloy was AA6063 aluminium alloy reinforced with 5 vol.-% Al2O3 and 5 vol.-% TiC particles. The particles were synthesized by self-propagating high temperature synthesis (SHS) technique. The composite was fabricated using stir casting method. General equations for predicting the effect of the applied load and sliding speed on wear resistance of the composite alloy were formulated using both ANN and DoE approaches.
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