Comparison between traditional project appraisal methods and uncertainty analysis applied to mining planning

Abstract

Long-term mining planning is a complex process which involves a large number of variables and uncertainties. Traditional discount cash flow (DCF) is usually used in the evaluation of mining projects. DCF includes net present value (NPV), internal rate of return (IRR), and profitability index (PI). A sensitivity analysis is usually carried out to evaluate the impact of the main variables on the project. Another way to measure uncertainties is through the Monte Carlo simulation (MCS). The objective of this study is to evaluate and compare the DCF methods and measure uncertainties through sensitivity analysis and MCS in the evaluation of mine sequencing. A case study of a phosphate mine project was used to chart the comparative study. In the results, NPV and uncertainty analysis through MCS were more consistent.

Financial risk analysis with uncertainties of phosphate ore beneficiation

“…Conventional NPV models assume that the value of each input parameter adopted as a unique correct value fixes all future outcomes. However, these parameters are usually stochastic and risky (Mun 2006; Chen 2011; Fontes 2020). Conventionally, the discount rate completely accounts for all risks, and immeasurable, or intangible, unknown factors are valued at zero.…”