The artificial neural network based prediction of friction properties of Al2O3-TiO2 coatings
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Abstract
Purpose - The purpose of this paper is to predict friction/wear properties of Al2O3-TiO2 coatings using artificial neural networks (ANN). Design/methodology/approach - Wear experiments were conducted in dry and acidic conditions. Wear loss values were determined and an ANN model was fixed in order to predict wear loss and friction coefficient values. Findings - Experimental and theoretical study results were well matched for wear loss and friction coefficient values. Research limitations/implications - The paper covers comparison of experimental and theoretical friction/wear results. Practical implications - A practical implication is that wear loss values can be predicted without further wear experiments. Originality/value - In this paper, the wear behavior of Al2O3-TiO2 coatings has been investigated, both experimentally and theoretically, for the first time.