By: Steve Burks

In the first two columns in a series of four, I suggested an enhanced approach to business planning and implementation in the minerals industry. In this, the third column, I focus on the application of simultaneous optimisation techniques across the nonmining portion of the value chain, drawing significantly on my recent experience working for Australia’s Whittle Consulting.

The nonmining steps in a mineral resource company are often not appreciated. This is despite the fact that they can significantly influence the mining schedule in a fully optimised value chain. To demonstrate this, Whittle Consulting usually tests the potential benefits of these steps one by one.

The operating cost model for the whole operation is reconfigured to focus on the variable- and fixed-cost elements. Variable costs are assigned to a specific physical attribute, such as tonnes of rock mined or ounces of gold produced. Fixed, or ‘period’, costs are linked to a specific period of time, usually a financial year. ‘Fixed’ annual costs frequently change from budget to budget.

A theory of constraints is then applied by assigning all the period costs to the bottleneck in the production chain. This encourages the optimised solution to reflect the combination of mining, processing and production schedules that will generate the most cash through this specific bottleneck. An outcome commonly seen in manufacturing, but novel to many mining industry operations, is that other sections of the value chain may therefore run at only a fraction of their design capacity because they are not the bottleneck.

Blending of run-of-mine and stockpiled ore before processing is typically done to ensure a consistent feed grade and facilitate ease of operation. In an optimised scenario, blending is more likely to be used to control impurity levels in the final product for the benefit of the downstream processes or to increase overall product value.

Conventionally, metallurgical operations are run using the same control parameters for an extended period and to maximise metal recovery. However, maximum early cash flow can sometimes be achieved by introducing a considerable amount of variability. For example, orebodies sometimes contain clearly differentiated zones of different minerals with different hardness and metallurgical performance. It can often make sense financially to push softer ore types through the milling and subsequent circuits at a faster rate, even if lower recoveries are achieved while this is done.

Operations also often aim to produce a fixed product grade or a series of products with little variation over time. It is usually the case that metallurgical recovery will be increased by reducing product grade for a given feed grade, resulting in a greater quantity of product. However, if the downstream process has limited capacity available, then a better financial option may be to sacrifice some recovery and produce smaller quantities of high-grade product from the primary concentrator. The optimal solution is likely to vary from year to year.

For bulk mineral products, such as coal or iron-ore, the available transport capacity for the products may have a significant influence on the overall operation. The best financial outcome is likely to be the one which maximises the use of the bottleneck, usually the rail line or the port, to handle the greatest possible amount of high-value products.

The steps described so far are all tested in turn and then in combination at the basic operational or design capacity specified by the owner. This is done to develop an optimal solution before considering the application of additional or alternative amounts of capital. There is an optimum size for any operation at which the net present value (NPV) will be maximised, provided that external limits are adhered to on items such as available capital, electrical energy, carbon emissions, and so on.

The outcome of an optimisation study is a report that identifies the potential impact on the NPV of each of the mechanisms tested, as well as the overall net effect of applying all the steps. The recommendations in this report then need to be implemented to achieve the benefits. In addition, the strategic potential can only be realised if the operation achieves its design efficiencies and the production capacity limits identified at each stage of the value chain.

In the fourth and final column of this series, to be published next week, I give suggestions on how the typical planning process for minerals industry enterprises could best be modified to both identify and realise the full potential for improvement.

Steve Burks, an Associate Director of Johannesburg-based MAC Consulting, a management consulting group specialising in mining, oil and gas, financial services and telecommunications suggests that this could be the case, and offers some suggestions about how the situation might be improved. Prior to joining MAC Consulting, Burks had completed 30 successful optimisation studies over the past four years in Africa on behalf of Australia’s Whittle Consulting. This in turn followed nearly 20 years spent working for Bateman Engineering where Burks was involved in feasibility studies, project delivery, technology commercialisation, change management and business acquisitions and start-ups for mining related operations and projects in many countries.