ENHANCED FRAGMENTATION ANALYSIS USING THE ROCK ENGINEERING SYSTEM APPROACH AND KUZ RAM MODEL FOR OPTIMIZING ROCK BLASTING

Abstract

Rock fragmentation is a key factor in blasting operations, as it significantly affects drilling and blasting costs, and the performance of downstream processes including loading, transportation, and crushing. Observations conducted at limestone quarry on the PT DAP jobsite indicated that the percentage of boulders produced ranged from 15.02% to 63.44%, with an average of 27.2%. Such variability in fragmentation size can hinder excavation efficiency and potentially disrupt production targets. Therefore, accurate prediction of rock fragmentation is crucial for optimizing blasting outcomes. This study evaluates the effectiveness of the Rock Engineering System (RES) model, which integrates 10 interacting parameters, in predicting blast-induced rock fragmentation. Twenty production blasting events were analyzed using field data, laboratory tests, and Split-Desktop software. The RES predictions were then statistically compared with actual field results and those obtained from the conventional Kuz-Ram model. The analysis revealed that the RES model achieved a coefficient of determination (R²) of 0.94, indicating a strong correlation between predicted and actual fragmentation sizes. Additionally, the model demonstrated a Root Mean Square Error (RMSE) of 8.46, suggesting a low margin of prediction error. These results confirm that the RES model provides more accurate and reliable fragmentation predictions compared to the Kuz-Ram method. In conclusion, the RES model offers a more effective tool for predicting rock fragmentation in blasting operations, supporting improved planning and control of mining activities to enhance overall production efficiency.