Title: An applied economic assessment and value maximisation of a mining operation based on an iterative cut-off grade optimisation algorithm
Authors: Antonio Nieto; Bruno Muncher
Addresses: Mining Engineering Department, University of Johannesburg, Johannesburg, South Africa ' Minerals Engineering Department, Penn State University, State College, PA, USA
Abstract: After demonstrating the importance of estimating available reserves (Muncher and Nieto, 2017), this paper focuses on the economic assessment and mine production optimisation using an iterative cut-off grade algorithm (Nieto, 2010). The maximisation iterative process increased the NPV by 40% and produced a 25% higher internal rate of return (IRR). The improvement of overall economic results, the government and local communities may also benefit from a reduced environmental and social impact, as an optimised cut-off grade reduces the mine life from 23 to 16 years. Furthermore, the economic viability of the project is analysed within different operational and economic scenarios. Three different sensitivity analysis regarding alternative values of processing capacities and gold prices, are evaluated. Results are analysed and discussed, indicating the overall advantages that this optimisation method offers. All currency figures are US dollars.
Keywords: cut-off grade; mining optimisation; mine valuation; mining innovation; net present value; mineral economics; mine planning.
DOI: 10.1504/IJMME.2021.121330
International Journal of Mining and Mineral Engineering, 2021 Vol.12 No.4, pp.309 - 326
Accepted: 09 Jan 2022
Published online: 04 Mar 2022 *