BackK-MINE’s stope optimization software streamlines underground mine planning, ensuring efficient ore recovery and maximized profitability. Using block model-based economic evaluation, the software identifies profitable mining zones, dynamically adjusts stope boundaries, and allows engineers to compare multiple optimization scenarios.
With structured clustering algorithms, K-MINE groups blocks into coherent stopes, adhering to predefined mining constraints while minimizing dilution. The software also integrates Equivalent Linear Overbreak Slough (ELAS) analysis, refining boundaries to prevent unnecessary waste extraction and ensuring maximum efficiency.
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K-MINE’s stope optimization software enhances underground mine planning with advanced structured workflows and block model-based economic evaluation. The process begins with block model data preparation, analyzing ore grades, economic values, and mining constraints.
The software automates economic evaluation and block filtering, ensuring only profitable blocks are considered for inclusion in the stope design. Unlike manual methods, K-MINE dynamically adjusts stope boundaries to optimize ore recovery and minimize dilution.
Using structured clustering algorithms, K-MINE groups blocks into coherent stopes, ensuring that each stope meets predefined mining constraints. The software integrates Equivalent Linear Overbreak Slough (ELAS) analysis, refining stope boundaries for maximum ore recovery and minimal dilution.
Engineers can evaluate multiple optimization scenarios, comparing different strategies to maximize profitability and efficiency. The software ranks scenarios based on economic indicators such as net present value (NPV) and extracted tonnage, providing a clear decision-making framework.
By combining automation, optimization algorithms, and 3D visualization, K-MINE replaces traditional manual estimation with a precise, data-driven approach to underground mining.
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