Neural networks analysis for estimating rock cuttability from rock properties

Twenty-two rock samples having different rock properties are subjected to a set of experimental program in the laboratories of Mining Engineering Department Istanbul Technical University. In the first stage, rock samples are subjected to a large program of rock mechanics tests. In the second stage, rock samples having size of 40 x 40 x 50 cm are subjected to full-scale rock cutting tests with a type of conical cutter using linear rock cutting machine (LCM) developed under NATO-TU Research program. Some predictor equations using regression analysis are developed to estimate the performance of mechanical excavators utilizing point attack tools. Artificial neural network (ANN) analyses are also performed to see whether it is possible to predict the performance of conical cutters more accurately than statistical analysis. The results indicate that ANN method yields more reliable predictor equations for cutting performance. The ANN models explained in this study will be further refined in future.