Bibliographic citations
Romero, M., Díaz, J. (2020). Aplicación del modelo estadístico de Monte Carlo en la predicción del precio de los metales y valor de mineral para evaluación de rentabilidad del proyecto minero Sofía D – U.E.A. María Teresa ejecutando el método sub level stoping con relleno hidráulico cementado [Pontificia Universidad Católica del Perú]. http://hdl.handle.net/20.500.12404/15950
Romero, M., Díaz, J. Aplicación del modelo estadístico de Monte Carlo en la predicción del precio de los metales y valor de mineral para evaluación de rentabilidad del proyecto minero Sofía D – U.E.A. María Teresa ejecutando el método sub level stoping con relleno hidráulico cementado []. PE: Pontificia Universidad Católica del Perú; 2020. http://hdl.handle.net/20.500.12404/15950
@misc{sunedu/2657163,
title = "Aplicación del modelo estadístico de Monte Carlo en la predicción del precio de los metales y valor de mineral para evaluación de rentabilidad del proyecto minero Sofía D – U.E.A. María Teresa ejecutando el método sub level stoping con relleno hidráulico cementado",
author = "Díaz Acuña, Jose Walter",
publisher = "Pontificia Universidad Católica del Perú",
year = "2020"
}
Nowadays, the statistical models play an important role in all industries, since they generate a greater level of confidence during the decision making, due to it is based on mathematical analysis which can predict various scenarios for a process. Such is the case of Monte Carlo simulation, a methodology based on random samples generation relying on one or more variables which are part of one process, mathematically parameterized, and whose result will expose different future scenarios for a particular event. The A.E.U. María Teresa, Minera Colquisiri S.A. property, intends to explore the "Sofía D" deepening project through the “Sublevel Stoping” extraction method using the Cemented Hydraulic Fill (CHF) at a rate of 1,600 tons per day (TPD) and that as of June 2019 it has 6,596,963 metric tons (MT) as mineral reserve with an average grade of 6.85%. In the described context, the thesis develops a route of the use of the Monte Carlo tool, applied to the price of metals, and its subsequent evaluation of profitability based on the project in question. The investigation consists of the following three stages: (1) Monte Carlo methodology, whose output is the simulation of different scenarios with respect to the Annual Gross Income (IBA) for 1,600 TPD between the years 2019 to 2032; (2) Profitability assessment, which seeks to calculate the profitability indicators, which are the Net Present Value (NPV) and Internal Rate of Return (IRR), our inputs are IBA, Capital Cost (CAPEX) and Operating Cost (OPEX); and (3) profitability indicators analysis, which determined an NPV of USD 99,902,835 with an IRR of 25.4% that demonstrate the viability of the project and its possible income during its operating time. Furthermore, Future scenarios were simulated in the 2,500 TPD case, where an NPV of USD 153,508,993 was obtained with an IRR of 21.9%, which in comparison with the indicators of 1,600 TPD is a more profitable one and consequently is recommended as a feasible operation alternative. In conclusion, has been demonstrated that the Monte Carlo method and its subsequent statistical analysis can work in synergy in the evaluation of the profitability of a project; not only because of its practice of the method but also because it allows to explore future events and to choose the best option for a particular operation.
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