Modelling Failure Pattern of a Mining Truck with a Decision Tree Algorithm

Abstract

This paper reports on the development of failure pattern recognition model for a mining truck. The model inputs, VIMS data collected in a mine, were processed using one of the Decision Tree algorithms, a module of the Intelligent Miner for Data software of IBM. The results indicate that the Decision Tree allows for identification and quantification of relations between the various types of VIMS data. As such, it can be used for development of a model that would allow prognosticating truck condition and performance. Full development of this capacity requires further research.