Extension of reliability information of Z-numbers and fuzzy cognitive map: Development of causality-weighted rock engineering system to predict and risk assessment of blast-induced rock size distribution

Blasting operations in surface mines have the primary purpose of fragmenting the rock mass into a size that is optimal and economically viable for the mine. This ideal size has an impact on every step of the mining operation, from loading and hauling through crushing and grinding. To put it another way, the economics of the mine or facility as a whole are significantly impacted by having the ideal size distribution. This research offers a causality-based rock engineering system (RES) for risk assessment and prediction of rock fragmentation generated by blasting in surface mines. The fuzzy cognitive map was utilized in the proposed approach in order to weight the RES in accordance with the reliability information provided by the Z-number theory. This model of the RES that is weighted according to causality and based on reliability is abbreviated as causality-weighted rock engineering system based on reliability (CWRESR). The construction of the model makes use of a database that was obtained from the Sarcheshmeh copper mine. The findings indicated that the overall risk level of fragmentation was somewhere between high and very high, with a vulnerability index (VI) of 69.73 cm. As a result, controlled blasting operations are strongly advised as a means of lowering the amount of risk. In addition, the suggested model was able to predict rock fragmentation with a coefficient of determination (R2) of 0.9462 and 9646 for the training and testing phase, respectively, demonstrating that the CWRESR model is superior to other models in its ability to predict rock fragmentation.