Decision Trees

1.1. Comparing Scenarios

You can run all the scenarios individually, just like what you did on the Practice First. The main parameters to compare them could be the NPV results and the mining sequence generated, which provide an overview of the difference that each change in parameters does on the results.

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2. How to Analyze multiple Scenarios

2.1. Increase in the value of copper

Analyzing first the scenario where there is a change in the economic value of the P1 process ("scn02-PriceUp"), values such as NPV will obviously differ. In this case, analyzing the NPV and the total movement (Process + Waste), it's possible to understand that a different mining sequence was generated which increased in 1 period more the mine lifetime. This market change has also increased cumulative NPV values based on its direct relation with the copper selling price.

The charts below were made with the help of MiningMath results in a simple sheet's software.

2.2. Adding an average grade limit

Now we can analyze the scenario where it was added a restriction in the average grade in the P1 process, using a minimum and a maximum limit of copper ("scn41-AvgCu").

The blocks that would be processed were more selected, the ones with higher or lower levels than the required would be blended together to respect the constraint and perform the sequencing. Notice that there is higher total production in each period, caused by the increase of the stripping ratio to meet the 30 Mtons of production and the average grade interval. A better stock pilling use is expected, in order to fulfill the plant capacity by using all the blending capabilities and decision making intelligence of the algorithm. In general, the main goal of MiningMath is to maximize the cumulative NPV in the shortest period as possible, considering the set of constraints provided.

The charts below were made with the help of MiningMath results in a simple sheet's software.

3. Building Decision Trees

You have experienced some of the usages of MiningMath, now it is necessary to understand in-depth how decision trees are made.

Mine project evaluation largely relies on technology from the 1960's, where a step-wise process is necessary along with time-consuming activities like pit-design, just to have one scenario. Evaluating projects with this approach could take from weeks to months of multidisciplinary work just to produce a few scenarios. This process is often guided by a few arbitrary decisions that may constrain the mathematical solution space, confining solutions to engineering expertise and judgment.

A global optimization scheduling can speed up this process of generating multiple scenarios for project overview prior to detailed work. MiningMath integrates the businessโ€™ areas and allows managers to improve their decision-making process by structuring their strategic analysis through multiple decision trees with a broader and optimized view of their projects, comprising constraints from different areas of the company.

The following video shows a few possibilities recognized only when seeing the available paths to create value. The video is oriented to technical daily usage but also covers subjects interesting to the managerial perspective. For the last case, skip straight to minute 15:23.

4. Apply to your projects

Now that you have played with the sample data, it's time to click on the button below and apply this optimizing strategy to your own projects!

These will be your next learning steps.

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