Data analysis solutions to improve blasting efficiency in mining

Abstract

Purpose. To build an identification model to determine the appropriate explosion parameters value with reasonable cost. To optimize blasting works design at each blast site with the calculation of delay time based on the model used. Methodology. Blasting for mining is an issue of utilizing the most of explosive energy in order to achieve the highest smashing ability and the smallest level of vibration. In modern explosive techniques, the total amount of explosive is divided into parts to detonate after differential time intervals. This solution creates interference between stress waves causing the durability of rock structures to be reduced and the blasting efficiency to be improved. Although delay time plays an important role in this method, so far its value is still calculated empirically at the blast site due to the irregular characteristic of the rock environment. Technical design parameters for explosion including delay time has been also determined from smart analysis software and simulation models. However, their applicability is limited because of high payments and strict implementation conditions. The method proposed in the study overcomes this drawback and its effectiveness is proven by the process of analyzing experimental data at Nui Beo Mountain of Vietnam. Findings. An identification model is developed based on the information including: explosion delay time value; average propagation speed of the vibration wave; maximum amplitude of the vibration wave. Originality. Basic data analysis software and an artificial neural network model are used. A new data analysis algorithm is established to determine the optimal explosion delay time value. Practical value. A simple and reasonable-cost solution is formed for improving the efficiency of blasting in mining.