Conference Proceedings
Orebody Modelling and Strategic Mine Planning SMP 2014
Conference Proceedings
Orebody Modelling and Strategic Mine Planning SMP 2014
Enhancing Risk Management in Strategic Mine Planning through Uncertainty Analysis
In a climate characterised by an ever increasing focus on cost reduction and maximising the utilisation of existing assets and infrastructure, understanding the uncertainty associated with alternative investment and operational choices becomes paramount to minimising the risk of making an ineffective decision. To assist in this process, TSG Consulting has developed an analytic framework to capture the underlying complexity of a mineral supply chain, and then quantify the impact of the uncertainty associated with the key drivers of business productivity. The technical basis of this approach follows three distinct steps: analyse the current system and identify the major factors that drive value build detailed models that can measure the response of the system to potential changes in the factors identified quantify the sensitivity of financial and capacity forecasts to these factors._x000D_
Each of the above steps draws on a different area from the field of applied analytics, namely: data analytics dynamic modelling and designed experimentation meta-modelling and optimisation._x000D_
Following the three-step approach described above ensures a rigorous modelling and analysis process is executed to support strategic mine planning decisions. The approach is equally applicable to the analysis of fully integrated system supply chains (pit-to-port), the evaluation of incremental capital investments to targeted areas of a supply chain, or when considering revisions to the operating philosophy of a system in the short term. The basis of each of the three analytic steps is explored in detail in this paper. The result is the definition of a structured mechanism for a business to actively manage risk and drive productivity as a component of the strategic mine planning process.CITATION:Fricke, C, Velletri, P and Wood, R, 2014. Enhancing risk management in strategic mine planning through uncertainty analysis, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 275-280 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Each of the above steps draws on a different area from the field of applied analytics, namely: data analytics dynamic modelling and designed experimentation meta-modelling and optimisation._x000D_
Following the three-step approach described above ensures a rigorous modelling and analysis process is executed to support strategic mine planning decisions. The approach is equally applicable to the analysis of fully integrated system supply chains (pit-to-port), the evaluation of incremental capital investments to targeted areas of a supply chain, or when considering revisions to the operating philosophy of a system in the short term. The basis of each of the three analytic steps is explored in detail in this paper. The result is the definition of a structured mechanism for a business to actively manage risk and drive productivity as a component of the strategic mine planning process.CITATION:Fricke, C, Velletri, P and Wood, R, 2014. Enhancing risk management in strategic mine planning through uncertainty analysis, in Proceedings Orebody Modelling and Strategic Mine Planning Symposium 2014, pp 275-280 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Contributor(s):
C Fricke, P Velletri, R Wood
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- Published: 2014
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- Unique ID: P201413030