Optimal Blast Design using a Discrete-Event Simulation Model in a Hard-Rock Mine

"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. IntroductionIn a modern hard-rock mine, various processes such as drilling, blasting, crushing, grinding and mineral liberation are optimized to increase productivity, a practice known as mine-to-mill (MTM) optimization. Blasting is important in MTM optimization as it is the first comminution process and has an impact on all downstream processes (Julius Kruttschnitt Mineral Research Centre, 1996; Nielsen and Lownds, 1997; Nielsen and Malvik, 1999; Chung and Katsabanis, 2000; Kim and Kemeny, 2011a; Kim and Kemeny, 2011b).Two main research topics have emerged in the area of blasting design: (1) identifying the optimal target blast fragmentation at each shot and (2) controlling the blast fragmentation for that target. As part of an MTM optimization study, Kim and Kemeny (2011a; 2011b) developed a site-specific blast fragmentation prediction model that can be used to identify the target blast fragmentation and can be incorporated into MTM optimization. They also reported methodology for assigning model parameters easily and with minimal human bias."