MiningMath

MiningMath

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One of the unavoidable steps for the next generation of Data Science and Artificial Intelligence technologies applied to mining

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Find articles, exchange experiences and learn secret tips to get the most out of MiningMath.

  • The end of cut-off grades as we know?

    The cut-off grade is the concentration of a mineral or metal required to classify materials as either ore or waste. Materials with a concentration above the cut-off are classified as ore, while anything below is classified as waste.
  • Understanding MiningMath’s scheduling stage

    MiningMath’s single-step methodology generates a diverse range of schedules straight from the block model, in a single-step! And your short-term requirements can also be accounted for within the same long-term run.Our software allows mining engineers to improve their strategic analysis through risk assessments that are...
  • Generate a diverse range of pushbacks straight from the block model

    With MiningMath, you can produce optimized, single-step pushbacks with controlled ore production and operational designs. This procedure is important to ensure the financial and operational viability of the mining project, as excessively large volumes can render the project unfeasible, while excessively small volumes can result in...
  • Gain more flexibility and ease in managing blocks with fixed destinations

    MiningMath optimizes destinations in a single-step, aiming to maximize the NPV of mining projects.
  • Bienstock-Zuckerberg Algorithm: Applicability and Limitations

    What is the Bienstock-Zuckerber (BZ) algorithm? The Bienstock-Zuckerberg (BZ) algorithm is an approach for solving large-scale, complex scheduling problems in the area of mixed-integer linear programming (MILP), such as those encountered in some direct block scheduling (DBS) formulations. First proposed here and here, the BZ algorithm...

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