Mining consultancy VBKom Projects notes that option analysis in capital-intensive projects for the mining industry is a challenge for project managers, in which business cases are commonly used as the tool to differentiate the expected value of options.

“The results of these business cases often contain much uncer- tainty and are unclear. This may lead to decisions favouring options with large amounts of uncertainty, rather than options with more certainty but a slightly less favourable business case.

“Where uncertainties in business case elements are too high, the options are, in many cases, piloted at great costs,” says VBKom Projects MD Eduan Pieterse.

To assist clients in eliminating the high piloting costs, VBKom Projects provides two classes of decision-making support services, which simulate the scenario first, at a cheaper price.

“The first class of decision support is risk-based decision support. It makes use of Monte Carlo simulations to iterate thousands of potential outcomes and provide a statistical basis for the baseline scenario,” says Pieterse.

Monte Carlo simulation, or probability simulation, is a technique used to understand the impact of risk and uncertainty in financial or project management cost and other forecasting models.

“Based on corporate risk policies, the baseline position can be adjusted accordingly by the provision of a statistically calculated contingency or factor. This has the effect of moving the baseline confidence percentile into the acceptable range of acceptable range of statistical certainty,” he explains.

He says this technique is most often applied to project capital budgets, estimates, schedules, deadlines and investment net present values, but has also more recently been applied in more technical areas such as capacity overflow determination and product specification breaches.

“The second class of decision support, simulation-based decision support, makes use of process simulation. The business processes are defined and simulated as a continuous or batch operation in a simulated real-time environment.

“This service allows clients to fully understand the effect that system constraints will have on the outcome of their projects, be they greenfield or brownfield. The factors that must be considered for integration with peripheral systems are highlighted, and design and process logic as well as assumptions can be tested with ease, at a low cost, compared to physically building a pilot plant and testing multiple scenarios,” says Pieterse.

He adds that mining options that can be evaluated through process simulation include heavy mining equipment fleet size options, route optimisation, mineral processing, cost optimisation, inventory location and volume optimisation and water balance management.

“Applying changes early in a project is always much more affordable than making costly modifications later in the project cycle, when finished work will have to be redone.”