Robustness can be defined as the ability of a system to resist change without adapting its initial stable configuration. Robust design methodology, which is widely accepted in the manufacturing industry, allows the establishment of robustness and reliability metrics in scenario analysis.
In the mining industry, a mine can be considered as a system with design parameters such as processing plant and mining capacities. Traditionally, a limited number of scenario iterations are performed in an attempt to determine optimal capacity values. An important strategic decision such as process plant capacity in particular is made during the very early stages of a mining study, often based on a low level of information. Lack of time and tools to run and analyse a larger number of possible scenarios for different design parameter combinations are usually the main reasons for not performing a full analysis. In addition, the uncertainty of other mining study input parameters creates more risk in decision-making.
With advances in technology, it is now possible to automate the process of generating several thousands of scenarios in an affordable and timely manner. This allows performing the results analysis and assessing robustness and reliability criteria within a reasonable time frame. It is possible to generate a surface of results based on the net present value (NPV) for each scenario. This surface will reflect the efficiency level of the capture of the economic rent for each production scale. In addition, each scenario can be tested under diverse conditions of volatility of other external variables such as prices, costs or recoveries for example.
This paper aims to establish a methodology that applies robustness criteria to determine the best scenario on several surfaces of value, which is then assessed with real data from a mining project. Obtained results demonstrate the advantages of using the proposed methodology in dealing with the above-mentioned multidimensional problems. It allows better decision-making on key design parameters and better control of the risks of a strategic mine plan.
Poblete, C J, González, M A, Romero, J A, Fuentes, D L and Abdrashitova, O, 2016. Use of Robust Design Methodology for Production Scale Definition in Open Pit Mining, in Proceedings Ninth AusIMM Open Pit Operators’ Conference 2016, pp 284–291 (The Australasian Institute of Mining and Metallurgy: Melbourne).