Economic Modelling And Optimisation Application In The Mining Industry

Cyest Corporation has been involved in economic modelling and optimisation with various mining clients within South Africa, and internationally, for the past 5 years. In the mining industry in particular, the relationships between variables that are controllable, and those that are not, and the physical and economic outcomes are complex and often non-linear. These relationships constitute an economic system. In the mining context, although many of the relationships can be accurately quantified on a ?single variable to single variable? basis, such simplistic relationships will not suffice in order to understand the dynamics of an entire mine. One has to specify and quantify the relationships between hundreds, if not thousands, of variables. Furthermore, in reality, these relationships change over time. This is the role of an economic model where all the relevant cause-effect relationships, within pertinent constraints, are accurately represented. Models that are used for optimisation must therefore capture the dynamics of the economic system in question as well as anticipate changes to the relationships between these variables. An accurate economic model is a prerequisite for successful optimisation. Optimisation entails the allocation or configuration of resources, within control of management, which will maximise (or minimise) a desired objective function. An optimal configuration (implying trade-off) of controllable variables therefore exists for a given set of assumptions that will yield a maximised objective function. Due to the multi-variant trade-offs required for optimisation, the concept of the ?Economic Surface? or ?Hill of Value? has been used to represent these optimisation outcomes and to discern the route to an optimal configuration. A good example of this is the volume versus cut-off grade trade-off that yields an optimal value for a particular shaft with its unique geological and economic assumptions. More recently, Cyest has extended these economic models to incorporate risk associated with variance in assumptions and inputs. This is termed DFA (dynamic financial analysis) and incorporates stochastic modelling and some of the latest actuarial techniques around modelling global assumptions (such as pricing and exchange rate). This paper will cover the theory around mine optimisation through some example case studies, and also explain the latest thinking regarding incorporating DFA.