الفهرس 
Title : Study of economic feasibility of phosphate ore beneficiation using financial risk analysis, modeling, and optimization with uncertainties
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Abstract
Mine is a risky project with an uncertain nature. The engineering assumptions and the related data from the ore deposit to market through cost and recovery estimations have their variability and uncertainty. Therefore, the business decision to invest capital in developing a mine and constructing a mineral processing plant and services is crucial.
Although, the net present values (NPV) can conclude the profitability and feasibility of a mining project, the uncertain nature of the mine and market indicates the investor’s need for proper quantitative risk analysis to get an accurate and reliable estimation of the NPV of the mining project, considering their risks and uncertain variables.
The conventional (deterministic) NPV excludes variability or uncertainty. However, the financial risk analysis can be used to give a mine realistic NPV evaluation and optimization using stochastic variables. The stochastic estimation of NPV incorporates uncertain parameters and risks to overcome the problem of obtaining a deterministic or single-point NPV.
The acute lack of knowledge related to any mine, costs, and market variables proposes the modeling using a uniform or skewed probability distribution. However, the availability of data reduces the considered scenarios and gives investors a clearer vision of the project assessment with a higher level of certainty with the inputs modeled with other distributions of probability.
This thesis develops a new dynamic model for financial risk analysis and optimization for Abu-Tartur phosphate ore beneficiation as an example, incorporating uncertainty to estimate the stochastic NPV using the @Risk 8.1 software.
The new model uses Monte Carlo (MC) simulation to generate stochastic and simulated data representing the uncertainty assessment for each variable as probability distribution functions, regarding which the data are actual, assumed, or researched. Probability distribution functions evaluate a large number of hypothetical scenarios with related uncertainties by searching in the solution space, giving more accurate results. It allocates a stochastic value to each uncertain variable between its lower and upper boundaries. A determined distribution function follows the frequency of each value.
The elimination of the mining project’s risk is not the ultimate. Every mining project has the most important stage from the money perspective, which is the optimization of NPV to maximize the expected profit yielded by the mine and minimize the net present value at risk (NPVaR). The optimization process comes down from the simulated NPV.
The interpreting sensitivity analysis establishes how to maximize the NPV by adjusting the data about the most sensitive parameters. Finding the optimum NPV, considering the simulated strategies and ultimate conditions, depends on finding the optimal way to meet the other recovery and production parameters adequately; while minimizing the related costs.
Abu-Tartur phosphate ores plateau, Western Desert, Egypt is selected as a case study for a better understanding and application of the newly developed model.
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However, the developed Economic Mine Value (EMV) model is general, as we could apply it to phosphate, coal, iron, gold, and any ore deposits. The aim is to build and verify the new EMV model with deposit optimum generated NPV with related risks and assessed uncertainties.
The NPV of Abu-Tartur beneficiation is evaluated using both the newly developed model and the conventional method. Also, the model runs the sensitivity analysis and optimization of NPV.
By comparing the deterministic NPV and the stochastic one, results showed that the deterministic evaluation estimates static NPV that has just a certain scenario. While a stochastic NPV was generated as a probability distribution with some level of the confidence interval. The probabilistic NPV estimated by the EMV model showed that the project is more economically viable than the static NPV (without uncertainty assessment) with a likelihood of about 53%. However, the static evaluation does not appropriately inform the decision-maker of the potential profit-making as well as loss-making in the project, as was indicated from the EMV model with about 4.7%.
Also, the EMV model stochastically runs a simulated sensitivity analysis and optimization process, seeking the maximizing of NPV while handling multiple decision variables and under the identified constraints that are ignored in the static evaluation. Optimizing the NPV through the EMV model by adjusting a larger production capacity with a lower capital expense (CAPEX) within the model constraints of price and NPVaR maximizes the expected NPV by about 35% with an improvement on the mining project with a recommended increase in the production capacity.
Furthermore, the EMV model can update the output with the new data of the related variables over time, enhanced with the building of the variable’s correlation and forecasting within the flowsheet and related mining project ten-year lifetime. The framework and guidelines of the new EMV presented model can enable the mining companies, investors, and managers to better make their future investment decisions. This study will deeply discuss and illustrate the fundamental differences between deterministic and stochastic models later in detail.
Conclusively, the mine and market conditions are inaccurate or optimistic estimations for investment in developing mines and quarries without considering of various risks, such as market, technical, economic, social, environmental, and political risks that can complicate the mining projects’ development. In particular, the Egyptian mining industry, especially the phosphate ore deposits, has an ongoing need for development. The research method and framework offer an opportunity for evaluating and optimizing investment in the Egyptian and global mining industry, considering the risks and uncertainty associated with the investments to gain more insights, into appraising the opportunity for the investment.