BUILDING INFORMATION MODEL FOR DRILLING AND BLASTING

Drilling and blasting are the major part unit in operations of mining or civil engineering projects. In spite of the best efforts to introduce mechanization in the mines, blasting continue to dominate the production. Therefore to cut down the cost of production optimal fragmentation from properly designed blasting pattern has to be achieved. Proper adoption of drilling and blasting can contribute significantly towards profitability and therefore optimization of these parameters is essential. This optimized parameter will be effective if a robust information model can be prepared based on the relevant practical data of the specific deposits. Initial rock mass characteristics data collection if collected during exploration stage is useful for selection of drilling machine and prediction of penetration rate – Key Performance Indicator (KPI). Further block model developed with geomechanical parameters will be useful during operation stage of mine. Geomechanical parameters are also important for design of slope in mine planning till final closure stage. Penetration rate, fragmentation, flyrock, ground vibration, air-overpressure (AOp) and backbreak are KPI for drilling and blasting. Explosives properties and selection of initiation system has impact on blast performance. There are various computational techniques such as artificial neural network (ANN) where various drilling and blasting (KPI) can be predicted accurately for yearwise budgeting and during operation stage of mine.

Computational techniques, Ground vibration, Air over pressure, Fragmentation, Penetration rate