Development of a fuzzy model to predict flyrock in surface mining

Flyrock is one of the most hazardous side effects of blasting operation in surface mining. This phenomenon can be considered as the main cause of casualties and damages. Inaccuracy of the available flyrock prediction empirical methods has caused utilizing of new methods such as fuzzy systems. In this paper a Mamdani fuzzy model was developed to predict flyrock in the Gol-E-Gohar iron mine of Iran. In this regard, a database including 490 datasets of the mine blasting operation was prepared from which about 20% was kept for testing the models. Performance of the fuzzy model was compared with that of the conventional statistical method. It was observed that efficiency of the developed fuzzy model is much better than the statistical model. Also, sensitivity analysis showed that powder factor and rock density are the most and least effective parameters on the flyrock, respectively.

Research highlights
► In the paper a fuzzy model was developed to predict flyrock in the blasting operation of surface mining.
► Prediction of flyrock is very important in the mining industry.
► Empirical models have shown poor performance to do the task.
► This research has proved capability of the fuzzy model to predict flyrock accurately.