Article #3: Generate Multiple 4D Simulations

In Article #1 of this series, I offered this definition of a tactical mine plan: A tactical mine plan turns the decisions outlined in your strategic plan into a schedule that will govern the mine’s day-to-day operations.

Article #2 discussed the differences between mining rules (these are your scheduling parameters: they must be followed in order for your schedule to match reality in the field) and mining targets (the levels you must achieve through your mining sequence to ensure profitability over life of mine).

My conclusion: To build a successful tactical mine plan, you must follow your rules while you chase your targets, which means tactical mining planning is almost always an iterative process.

Today’s scheduling tools use heuristic blending algorithms to choose which blocks get mined/when in order to meet your specific material ratio and quality targets. They also allow you to produce virtually unlimited iterations of short- and long-term schedules that provide useful information about things like material movements on a period-by-period basis.

The next step

Once you have decided on two or three possible schedules — ones that both follow your mine rules and meet your mine targets over the life of the mine — it’s time to test those schedules against each other. And the best way to do that is to generate 4D (3D plus time) simulations of each schedule.

Here I am going to again go back to a couple of things I said in the first article of these series:

Scheduling mine operations requires hundreds if not thousands of inputs, and if one input changes, a tiny decrease in tonnage, for example, it will have a cascading effect on some if not all of the others.
It can be difficult for planning engineers to fully understand the relationships between inputs and outputs at a mining operation. They might intuitively understand the downstream effects of, for example, increasing the production rate, but the nature of mining operations is often so complex that, without a comprehensive model, it’s difficult to really know what effect tweaking that rate may have.

Simulations are necessary because, while your targets will guide the mining sequence toward a desired grade or stripping ratio, they may not reflect other important mine planning outcomes, such as stockpile balances, haulage resource allocations, or costs and revenues.

4D simulations that link a time schedule with outcomes will illustrate how the whole project would or could work.

Time to play “what if?”

Unlike manual comparison, an automated, multi-dimensional simulation allows you to vary your inputs and monitor your outputs a virtually limitless number of times until you come up with a schedule that’s optimised not only for targets but also for external factors, such as cost or risk — giving you, the mine planner, a lot of control.

For example:

you get to define what “optimum” means
you get to “see” the true relationships between inputs and outputs, and compare them based on your own measurement of risk, and
you have the evidence you need to justify your choice of the “optimum” mine plan.

Plus you have helped your mine reduce the risk of costly mistakes and significantly increase the probability of success.

To end this series …

I am planning to talk about the importance of preparing financial models for your tactical mine plan and sharing your plan with all stakeholders.

Let me know if there is anything else related to tactical mine planning that you’d like to learn about and I will add it to this series.

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