MiningMath

MiningMath

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With MiningMath there is no complex and slow learning curve!

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Estimated reading: 4 minutes 1939 views

In order to take the maximum of MiningMath’s Optimization we recommend this flow through our Knowledge Base. It will guide you step-by-step in order to integrate multiple business’ areas and to improve your strategic analysis through risk assessments unconstrained by step-wise processes. 

Set up and first run

  1. Quick Check: Here you’ll have all the necessary instructions to install, activate and run MiningMath.

  2. How to run a scenario: Once everything is ready, it’s time to run your first scenario with MiningMath so you can familiarize with our technology!

Find new results

  1. Playing with pre-defined scenarios: Each change in a scenario opens a new world of possibilities, therefore, it’s time to understand a little more about and see it in practice, playing with pre-defined scenarios.

  2. Decision Trees: Decision Trees provide you a detailed broad view of your project, allowing you to plan your mining sequence by analyzing every possibility in light of constraints applied to each scenario, which options are more viable and profitable to the global project, as well as how these factors impact the final NPV.

Understand the technology in depth

  1. Current best practices: Here we go through the modern technology usually employed by other mining packages. It is important to understand these in order to comprehend MiningMath differentials.

  2. MiningMath uniqueness: Now that you’ve practiced the basics of MiningMath, and understand how other mining packages work, it’s time to get deep into the theory behind the MiningMath technology.

  3. Interface Overview: It’s time understand our interface overview with detailed information about every screen and constraints available in MiningMath. Home page, Model tab, Scenario tab, and Viewer for a better understanding of the possibilities.

Using and validating your data

  1. Formatting the Block Model: Learn how to format your block model data and use it in MiningMath.

  2. Importing the block model: Go through the importation process and to proper configure your data.

  3. Economic Values: MiningMath does not require pre-defined destinations ruled by an arbitrary cut-off grade. Instead, the software uses an Economic Value for each possible destination and for each block. After your data is formatted and imported into MiningMath, you may build your Economic Value for each possible destination.

  4. Data Validation: Once your data is set, it’s time to validate it by running MiningMath with a bigger production capacity than the expected reserves. Thus, you will get and analyze results faster.

  5. Constraints Validation: Continuing the validation, start to add the first constraints related to your project so that you can understand its maximum potential.

Improve your results

  1. Integrated Workflow: Each project has its own characteristics and MiningMath allows you to choose which workflow fits best in your demand and to decide which one should be used.

  2. Super Best Case: In the search for the upside potential for the NPV of a given project, this setup explores the whole solution space without any other constraints but processing capacities, in a global multi-period optimization fully focused on maximizing the project’s discounted cash flow.

  3. Optimized Pushbacks: Identify timeframe intervals in your project, so that you can work with group periods before getting into a detailed insight. This strategy allows you to run the scenarios faster without losing flexibility or adding dilution on the optimization, which happens when you reblock.

  4. Optimized Schedules: Consider your real production and explore scenarios to the most value in terms of NPV.

  5. Short-term Planning: Now that you built the knowledge about your project based on the previous steps, it is time to start the integration between long and short-term planning in MiningMath. You may also optimize the short-term along with the long-term using different timeframes.

Export your results

  1. Exporting Data: After running your scenarios, you can export all data. Results are automatically exported to CSV files to integrate with your preferred mining package.

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