Tribological Behavior of Ultra-High Molecular Weight Polyethylene Polymer with Artificial Neural Network Modeling

Abstract

This study presents the tribological properties, wear and friction, of ultra-high molecular weight polyethylene under conditions of dry sliding and Hank’s balanced salt solution lubrication. A pin-on-stainless steel disc apparatus was used for the friction and wear tests. Applied load conditions were 38, 50, 88, 100, 138, and 150N. Sliding speed conditions were 0.4, 0.5, 0.8, 1.0, 1.2 and 1.5 m/s. The results show that the coefficient of friction and the wear rate values decrease with the increase of applied load. The coefficient of friction and the wear rate values were highest under the dry sliding condition for the ranges of the sliding speed values and the applied loads tested in the study. In addition, the applicability of artificial neural networks (ANN) for predicting both the coefficients of friction and wear rate values of the material in different sliding conditions was studied. The neural network results were in agreement with the experimental results for the wear rates and coefficients of friction