This paper reports on the development of a simulation-based framework for obtaining optimal blast design parameters for a hard-rock mine. To do this, a conventional medium-sized hard-rock mine was taken as a case study. The mine has two pits containing hard and soft rock types. The proposed framework contains a combination of regression analysis using Excel software by Microsoft and discrete-event simulation using Arena software by Rockwell Automation, applied to construct a model of the material-handling network of the mine. Specifically, blasting parameters are estimated by Excel-based regression analysis, processes including blasting and haulage from pits to crushers are modeled by a Forward Blasting simulation submodel, and material-handling operations including crushing, storage in stockpile, and haulage via conveyors and into SAG and ball mills are modeled by a Crusher to Ball Mill simulation submodel. A Reverse Blasting submodel is then used to obtain the optimum blast design corresponding to a target P80 particle size. Using the proposed framework, an economic analysis was performed to demonstrate the cost savings that could be realized for each rock type as a function of specific explosive energy.
|Original language||English (US)|
|Number of pages||7|
|Specialist publication||Mining Engineering|
|State||Published - Nov 2015|
ASJC Scopus subject areas
- Geotechnical Engineering and Engineering Geology