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


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Training Presentation


John is a mine planning engineer working on Marvin deposit. He’s conducting the long-term production scheduling plan and is concerned on what would be the best scenario to optimize Marvin’s operations.

The mine has some constraints, such as slope angles defined block-by-block and a default value of 45 degrees for blocks missing information. The total movement is limited to 60 Mt/yr.

Part 1

  1. Formateconomic values, and import this Marvin data. Save it as MMCI_YourName_Marvin.

  2. Choose your own economic parameters and fill the Table 1b to simulate a process B.

Figure 1: Block model format

Part 2

Use the following steps to evaluate your project:

Now that you know MiningMath is able to easily run multiple scenarios, you should play with the remaining parameters, evaluate the results and bring a proposal for the board. You should:

  1. Download Screencast O-Matic or equivalent screen recording software.

  2. Prepare a presentation (ppt or docx), which could be structured by answering the following questions:

    a) What is the goal of your evaluation?
    b) How did you use MiningMath to achieve your goal? Which were the features used? What was the methodology used to get to your results
    Why have you got such results?

  3. Record it as if you were reporting your analysis to the board. Upload it on YouTube as public. The video should be limited to 5 minutes.

  4. Send the link, materials, and the Marvin data used to your teacher.


  1. What are the main resources of MiningMath viewer and which are the output files?

  2. Could market changes be considered based on different ore selling prices throughout time? If yes, how?

  3. Is it possible to forbid the optimization to access some specific region? If yes, which feature could be used?

  4. Which geometric features could be used to get results accordingly with the operational needs?

  5. What are the benefits of building decision trees?

  6. What are the main differences between Lerchs-Grossmann/Pseudoflow and DBS methodologies?

  7. What is the importance of considering a discounted cash flow on the optimization decision-making process? Does the value of money through time impact the mining sequence?

  8. Could the optimization handle multiple destinations? Over 2 processing plants? One stockpile for each with maximum capacity?

  9. Could production ramp-ups be part of the optimization constraints?

  10. Is it possible to control the average of a given variable, such as grade, haulage distance and etc.? How many properties can be controlled? Is it possible to change them over the mine's life?

  11. How does the cut-off grade policy work on MiningMath?

  12. What are the main validations before running a scenario?

  13. Can MiningMath run more than one scenario simultaneously?

  14. Which are the 3 main suggestions of the integrated workflow?

  15. Is it possible to generate a short term planning using MiningMath?

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