Abstract

The application of the Monte Carlo technique to production planning and everyday economic decisionmaking in mine production management is demonstrated. The logic is detailed using an example of underground production with continuous miners (CMs) and truck haulage. It is argued that availability of equipment and personnel are the predominant variables influencing mine output and productivity and that those availabilities may be well represented by binomial probability distributions. The probabilistic model is implemented in a standard Excel® spreadsheet with Palisade's @Risk add-on to facilitate simulations. Starting from model calibration against data obtained from a mine's annual reports, some general interdependencies of availability, utilization, productivity, and costs of production processes are outlined. Finally, several possible options and their consequences as regards production improvements are explored.

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