Browsing by Author "Nehring, Micah"

Now showing 1 - 3 of 3
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    Evaluation of the impact of commodity price change on mine plan of underground mining
    (Elsevier, 2015-04-15) Salama, Abubakary Juma; Nehring, Micah; Greberg, Jenny
    Fluctuations in commodity prices should influence mining operations to continually update and adjust their mine plans in order to capture additional value under new market conditions. One of the adjustments is the change in production sequencing. This paper seeks to present a method for quantifying the net present value (NPV) that may be directly attributed to the change in commodity prices. The evaluation is conducted across ten copper price scenarios. Discrete event simulation combined with mixed integer programming was used to attain a viable production strategy and to generate optimal mine plans. The analysis indicates that an increase in prices results in an increased in the NPV from $96.57M to $755.65M. In an environment where mining operations must be striving to gain as much value as possible from the rights to exploit a finite resource, it is not appropriate to keep operating under the same mine plan if commodity prices alter during the course of operations.
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    Financial analysis of the impact of increasing mining rate in underground mining, using simulation and mixed integer programming
    (Journal of the Southern African Institute of Mining and Metallurgy, 2017-04) Salama, Abubakary; Nehring, Micah; Greberg, Jenny
    This paper challenges the traditional notion that mine planners need to plan production so as to incur the lowest mining cost. For a given mine configuration, a mine that increases its mining rate will incur increased mining costs. In an environment in which operations are fixated on cost reduction, a proposal that increases costs will not be readily accepted. Such a proposal requires financial justification-the increase in costs might be recuperated by the additional production. This paper evaluates the net present value (NPV) across a range of copper prices for two underground orebodies located at different depths, using a production rate of 300 kt per quarter and a scenario that introduces additional equipment and costs for 450 kt per quarter. The evaluation was based on the changes of NPV for the orebody located at a shallow depth compared with the orebody at a greater depth. Discrete event simulation combined with mixed integer programming was used for analysis. Unlike traditional sensitivity analysis, this study re-optimizes the mine plan for each commodity price at each production rate. The results show that, for the low mining rate at the final copper price, an NPV of A$1530.64 million is achieved, whereas an NPV of A$1537.59 million is achieved at a higher mining rate. Even though pushing mining rates beyond traditional limits may increase mining costs, this option may be beneficial at certain commodity prices, particularly when prices are elevated
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    Operating value optimisation using simulation and mixed integer programming
    (Taylor & Francis, 2013-04-19) Salama, Abubakary Juma; Nehring, Micah; Greberg, Jenny
    Mining operations around the world will increasingly need to operate at greater depths. This significantly influences the complexity of ore extraction and ore transportation to the surface. The increase in mine depth leads to increases in haulage distance from mine areas to the mine surface. This results in an increase in energy costs to haul material further. Due to the increasing cost of future operations, the choice of the haulage method becomes an important factor in the optimisation of the mine plan. The haulage process is one of the most energy intensive activities in a mining operation, and thus, one of the main contributors to energy cost. This paper presents the comparison of the operating values of the mine plans at depth levels of 1000, 2000 and 3000m for diesel and electric trucks, shaft and belt conveyor haulage systems for the current and a predicted future energy price scenario. The aim is to analyse the impact of energy requirements associated with each haulage method, as well as the use of alternative sequencing techniques as mine depth increases. This study is carried out using a combination of discrete event simulation and mixed integer programming (MIP) as a tool to improve decision-making in the process of generating and optimising the mine plans. Results show that energy cost increases across each haulage method at both current and future energy prices, with increasing depth. This study thus provides a broad and up to date analysis of the impact on operating values that may be experienced with the use of the main haulage systems available at present. Also, the study shows how the combination of discrete event simulation and MIP generates a good tool for decision support.