The arti?cial neural network based prediction of friction properties of Al2O3-TiO2 coatings

Author： Cetinel Hakan  

Publisher： Emerald Group Publishing Ltd

ISSN： 0036-8792

Source： Industrial Lubrication and Tribology, Vol.64, Iss.5, 2012-08, pp. : 288-293

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

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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.

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