AN UNCERTAINTY ASSESSMENT MODELING FOR DEVIATIONS BETWEEN LONG- AND SHORT-RANGE PRODUCTION PLANS AT SURFACE METAL MINES

Date

2023-7-07

Author

Tekbey, Tolga Batuhan

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Surface mining is the dominating mining method employed for extracting near-surface economic minerals. Production planning in surface mines plays the most vital role in different ranges of horizons that can be divided into strategic or operational levels. Strategic (long-term) plans or decisions, affecting the Net Present Value of the project directly, decide on waste or ore mining blocks to be extracted in annual periods generally, while tactical and/or operational (mid- or short-term) plans decide on their daily implementation plans in the site. Mining projects are usually considered highly uncertain and risky due to the nature of the epistemic and aleatoric variables and the cost of obtaining information about them. Although some computational tools are available to evaluate and optimize long-range plans of surface mines to facilitate operational applicability in shorter ranges, various neglected or underestimated uncertainties in mining areas can cause drastic deviations from planned production targets. If the underlying factors and causes of these uncertainties are not explained and considered enough in the long-term planning phase, it will be inevitable to experience unfavorable results as deviation from the spatial advance of production area, the tonnage of targeted ore as well as waste production, and the targeted amount of final throughput. Therefore, sources and ranges of uncertainties, their aleatory or epistemic behaviors, occurrence frequencies, and their effects on the deviations should be considered holistically with factors showing how risky the plan is. At this point, the primary purpose of this thesis study is to develop an uncertainty assessment methodology covering fuzzy fault tree analysis and discrete-event simulation to explain quantitatively the uncertainty factors leading to deviations from long to short-range production plans of surface metal mines. In this regard, a Fuzzy Fault Tree Analysis (FFTA) has been conducted over the data collected from mine planning experts to determine the corresponding twenty-one uncertainty factors classified under geology, economy, operation, and external and their severity and frequency intervals. The analysis showed that various geological, operational, and external factors could explain 93% of the deviations in a long-term plan. In addition, grade itself can cause around 14% of deviations among all twenty-one factors. Following the FFTA, a Discrete Event Simulation (DES) algorithm was developed by considering the most effective and applicable uncertainty factors. The developed DES comparatively examines deterministic and stochastic long-term planning by monitoring production indicators. In its implementation for a hypothetical case, a drop of 0.4M tonne production and 140 koz gold were observed for 3M tonnes of production with a gold pour guidance of 435 koz where multiple influential uncertainty factors are available in the area, causing almost the worst-case short-range production scenario.

Subject Keywords

Uncertainty Assessment, Decision Support Technique, Fuzzy Fault Tree, Discrete Event Simulation, Surface Mine Planning

URI

https://hdl.handle.net/11511/104697

Collections

Graduate School of Natural and Applied Sciences, Thesis