Get the NPV upper bound better than the Best Case scenario!

Short-term Planning

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MiningMath allows the integration between long and short-term. By running the Best Casesurfaces to guide the optimization were generated and they could be used as a guide based on the NPV upper bound. The Exploratory Analysis provides insights on what could be the challenges of our project and also operational designs that could be used in further steps. At last, we obtained a detailed Schedule by using, or not, a surface, which could be the final pit or any intermediary one, as a guide.

Considering this workflow, now you may have enough information on a reasonable long-term view to enhance the adherence/reconciliation of your plans. You could choose a surface and use it as force and restrict mining to refine everything inside it. Remember that Force Mining is responsible for making the mining achieve at least the surface inserted, which means that all the material inside its limits should be extracted, respecting the slope angles, while Restrict Mining aims to prohibit the area below the surface inserted to be mined until the period in which it has been applied.

Thus, MiningMath will reach this exact surface in the time-frame required and enable you to test different geometries, blending constraints, and any other variable that could be required in the short-term planning without interfering in the long-term overview. Additional helpful features in these refinements are the concepts of mining fronts and the design optimization, based on surfaces modification, that could be done respecting all the parameters and generating results accordingly with your needs.

Figure 1: Results generated using different helpful features.


Parameters Value
Custom factor (0.5)
Processing capacity
5 Mt per semester
Total movement
20 Mt per semester
Vertical rate of advance
60m per semester
Minimum Mining
Bottom width
Force and Restrict Mining Surface
Surface005 from Schedule Optimization
Stockpiling parameters
Play with steeper slope angles in the short term?

Table 1: Set of constraints example (1).

Results examples

Further details

The example above used fewer constraints, geometries were changed and the average grade was let free. It is very helpful to define the early years based on a semester timeframe, which can assist you to manage stocks and any other variables in the firsts 3 years, for instance. Note that the period ranges on MiningMath are based on the timeframe selected, therefore, you should adjust your variables accordingly with this value.

When we use Force+Restrict, we are telling the optimizer to break this volume into pieces and that it must mine this volume entirely, even if it is waste, so that the long-term view is respected. This way, you keep regarding the whole deposit while deciding what to do in the first periods. The approach here is quite different than a set of Revenue Factors for a series of LG/Pseudoflow runs, followed by adjustments to find pushbacks without math optimization criteria. It is worth mentioning that this kind of suggestion must be only applied at the beginning or at the end of the life of mine, since Force+Restrict Mining surfaces used in intermediate periods could interfere directly with the results.

Using timeframes

Another strategy is to optimize the short-term along with the long-term using different timeframes. In this approach, the integration between the short and long term visions is made in the same optimization process, facilitating the analysis and strategic definitions.

It is possible to consider:

  • shorter time horizons (weeks, months, quarters...) for the initial periods of the operation;

  • annual plans as far as needed, for a precise definition of discounted cash flow;

  • less detail for longer time horizons. They need to be considered in the overall view of the mine, up to exhaustion, but they consume optimization processing time that can be more focused on the early years of operation.

Thus, there is value maximization at the strategic level, and feasibility at the tactical level simultaneously. In addition, there’s minimizing compliance and reconciliation problems, as well as improving communication between teams, by working in an integrated system.

On this strategy, each period range will represent the time interval chosen in the timeframe, and discount rate will be adjusted in alignment with the time interval choice. Other constraints such as production and vertical rate of advance (VRA) must be adjusted to match each interval on the period ranges.

In order to clarify this strategy, Table 2 and Figure 9 present a possible list of constraints for an example using timeframes:

Table 2: Set of constraints for a timeframe example.

Constraints chosen in the interface for a timeframe example.
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Short-term Planning

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