The artificial neural network based prediction of friction properties of Al₂O₃‐TiO₂ coatings

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.

Citation

Cetinel, H. (2012), "The artificial neural network based prediction of friction properties of Al₂O₃‐TiO₂ coatings", Industrial Lubrication and Tribology, Vol. 64 No. 5, pp. 288-293. https://doi.org/10.1108/00368791211249674