Understanding mine planning: a value-creation perspective
By Mathew Mamina
The idea of mine planning and design, as imagined by many, is not all about colorful 3D solids and fascinating animations but involves a much more significant objective – the creation of value. Although this objective is much more explicitly pursued during the strategic planning process, it is also an integral part of tactical/operational planning. This being the same universal objective of all business endeavors; mine planning can therefore be described as more of an entrepreneurial activity; one whose goal is to ensure any mining operation creates value during its life despite all associated complexities in the form of uncertainties and constraints. The mine planner’s decisions are always guided by the value creation goal constrained by factors that include but are not limited to safety, the operating environment, geological structures, and geotechnical characteristics of the deposit. In addition to technically sound designs in the form of the aforementioned 3D solids and animations, the mine planner should be able to clearly ascertain how each decision creates or destroys value; and must mentally mine the deposit in a safe and profitable manner before the actual execution of the mine plan commences.
Mine planning can therefore be described as more of an entrepreneurial activity, one whose goal is to ensure any mining operation creates value during its life despite all associated complexities in the form of uncertainties and constraints.
The two greatest challenges in this endeavor are that (1) it is close to impossible to know all the variables that impact the value creation goal with certainty and (2) systems in a mining operation are interdependent and cannot be treated in isolation from each other. The former challenge requires that the mine planner be well aware of what the future holds mainly in terms of the extent to which uncertainty in deposit geology and metal markets will affect the mine’s decisions and its value. The latter challenge mainly requires rational trade-offs and the concept of optimization further addressed in the paragraphs below.
The uncertainty challenge has been traditionally addressed through the application of better estimation and forecasting techniques, scenario analysis, sensitivity analysis, and to a lesser extent, Monte Carlo simulation. Although computing power has allowed the application of sophisticated mathematical methods in estimating deposit grades, forecasting commodity prices, and mining costs, it remains close to impossible to accurately predict the future. This does not mean, however, that forecasts have to be exact but whenever the market or ore grades assume unanticipated values, tough decisions are made in an ad hoc manner and the results can be sometimes catastrophic leading to the closure of a mine at worst. Although the traditional risk analysis tools, that is scenario and sensitivity analysis, are useful in telling the mine planner what may happen to a mine’s value in the worst-case scenario, in most cases no systematic measures are really put in place to respond to such a scenario. Rather more resources and time are dedicated to increasing confidence in the forecasting of those variables to which value is highly sensitive.
For instance, in cases where value is highly sensitive to grade, which is the majority of cases, more resources will be dedicated towards the acquisition of more geological data. In other cases where value is highly sensitive to the commodity price and mining costs, efforts are directed towards the use of better forecasting techniques. Although these endeavors can significantly increase confidence in estimates, there still remains some degree of uncertainty which the mine planner has to quantify and manage and Monte Carlo simulation becomes a useful tool. By using probabilistic distributions of variables instead of static values in the determination of a project’s value, Monte Carlo simulation yields a range of values (NPVs) with their corresponding probabilities of occurrence. In this case, uncertainty is quantified as the probability that a certain value (NPV) will be achieved, but managing it becomes another process that can be executed in a systematic proactive manner or in a subjective way. Managing uncertainty proactively and systematically can be achieved through the real options analysis approach which attempts, after quantifying uncertainty, to place a value on the flexibility of a mining operation to respond to unexpected events and evaluates if it’s worthwhile to invest in measures that ensure future flexibility of an operation. Since this is an emerging topic in mine planning which requires adequate attention, I will explore it more in the subsequent articles but for now, I will move on to how the challenge of interconnected systems can be addressed in mine planning.
Because every mining operation consists of different interconnected systems, both physical and non-physical, decisions on each system can not be made in isolation but rather by assessing the impact on the other systems and ultimately the value. This implies that the value creation goal is pursued through trade-offs between different systems. One of the most fascinating trade-off at the strategic planning level is that between the production rate, capital investment, and the life of mine. In as much as a higher production rate can yield more revenue, a larger capital investment is also required and the life of mine is shortened. This adds to the already existing challenge of sourcing capital in the mining industry, increases project risk and with a shorter life, the mine can miss out on future commodity price cycle upsides. Such a trade-off arises because unlike the manufacturing and other production industries, the mining industry deals with a finite resource. Whereas the production rate and annual profit maximization in other industries would have no bearing on the life of the operation, in mining it has an impact. It is for this reason that while the goal/ objective in manufacturing can be profit maximization, it has to be NET PRESENT VALUE MAXIMISATION in mining.
With a shorter life, the mine can miss out on future commodity price cycle upsides.
To illustrate this simply, a ballpoint producing company can maximise its profits in a single year by producing and selling as much pens as it can and this may not affect the number of pens it produces 2,3 or 5 years from today and it can still recoup its capital investment over several years. However, if the same company had a finite number of pens to be dug from underground, producing the maximum possible number of pens in one year would mean that the pens would be depleted and there would be no pens to produce or sell in subsequent years. A better strategy would be to come up with a yearly ballpoint production rate that maximises the NET PRESENT VALUE of extracting all the underground ballpoints over a finite period of time. The latter strategy is justified in that (1) the net present value takes into account capital invested (2) if the price of ballpoints were to rise in a year or two years’ time, the company has an opportunity to create more value than if all ballpoints were depleted in one year (3) a phased investment approach (less risk exposure) can be adopted without the pressure to recoup huge capital investments in a year (4) the market controls what can be sold in a certain period (5) a compromise of technical factors critical to safe extraction can lead to more risk exposure (6) socio-economic impacts of a short mine life are minimized. In making strategic decisions, the mine planner should therefore always evaluate the impact of any policy/decision (cutoff grade, production rate, mining sequence etc.) on the NET PRESENT VALUE.
This brings us to the issue of optimization as part of the planning process. Simply put, optimization entails adjusting policies (decisions) to satisfy/achieve a well-defined objective which is usually value maximization in mining as explained above. As an example, the decision on which cutoff grades to use over the entire life of mine is made in such a way that the maximum value is realized from extracting the resource. In this case, the cutoff grade is optimized to maximizevalue. Similarly, the production rate and mining sequence decision are optimized to maximize value. This goes down to other decisions that contribute to value in a direct or indirect way. Operational decisions, for instance, are optimized to minimize cost or to maximize productivity (a function of production rate and efficiency).
While the goal/ objective in manufacturing can be profit maximization, it has to be Net Present Value maximization in mining.
During the design phase, steep slope angles may be desirable for a lower stripping ratio and higher project values, but this also increases the likelihood of slope failure as the pit deepens. An optimum decision has to be made on the slope angle with a factor of safety that ensures pit stability throughout the life of mine while maintaining favorable striping ratios. In an underground instance, the mine planner’s job is not only to simply design a technically sound underground opening that, but one which satisfies the requirements of the other operational systems and is the least cost design out of all the other possible designs which could have been implemented. Ultimately, the value objective achieved through optimization, or in simple terms, through ensuring that every design, planning and operational decision either minimizes cost, maximizes productivity or ultimately maximizes the project NET PRESENT VALUE.
Mathew Mamina is a mine planning and mineral economics researcher based at the University of Zimbabwe and can be contacted via email at firstname.lastname@example.org.