The effect of geological uncertainty on achieving short-term targets: a quantitative approach using stochastic process simulation

multiple excavators producing multiple products of raw materials are highly complex and exhibit strong interdependencies between constituents. A network of conveyor belts is used for transportation of the extracted materials to different waste dumps or the coal stockpile. Optimal decision-making in short-term planning and production control are impacted mainly by geological uncertainty associated with incomplete knowledge of the coal deposit represented in the reserve block model. These uncertainties cause deviations from expected process performance. For more robust decision-making, understanding the impacts of these stochastic elements plays a key role. Techniques of stochastic process simulation, whether discrete, continuous, or combined (Kelton and Law 2000), provide a powerful tool for measuring the performance indicators of a complex system. In the past few years there has been significant development in the applications of process simulation in the mining industry. Panagiotou (1983) described the application of the simulation program SIMPTOL for opencast lignite mines that use bucket wheel excavators (BWEs), conveyors, and stackers. The main objective was to select and match the equipment to fit material characteristics while meeting production requirements and mine profiles. Michalakopoulos et al. (2005) presented a simulation model of an excavation system at a multi-level terrace mine using the GPSS/H simulation language. The principal model output variables are production and arrival rate of product and waste at the transfer point. Michalakopoulos et al. (2015) utilized Arena simulation software for the simulation of the Kardia Field mine in Greece. Validation of the results illustrates an acceptable agreement with the actual data. Fioroni et al. (2007) used discrete tools for simulation of continuous behaviour for modelling the conveyor belt network of a large steelmaking company. The authors proposed a modelling approach to the flow process that uses portions of materials and treats them as discrete entities in simulation modelling. The results demonstrated that this technique was valid and successful. Salama et al. (2014) used a combination of discrete event simulation and mixed integer programming (MIP) as a tool to improve decision-making in underground mining. The proposed method uses the simulation approach to evaluate the operating costs of different haulage system scenarios and obtains the cash flows for input into the MIP model. The effect of geological uncertainty on achieving short-term targets: a quantitative approach using stochastic process simulation