Methodological framework outlines a federated digital twin architecture for mining operations, highlighting human-in-the-loop verification and engineering accountability.
The problem with most solutions in the field of Digital Twins for mining is the gap between "advanced analytics" and real engineering accountability. How can we integrate geomechanics, metallurgy, and financial planning into a single loop without losing control over safety? In the new preprint "Mining AGI Platform — Volume 0: Reference Architecture", I have systematized the approach to creating a federated system of Digital Twins. Key focus — Evidence-Based Engineering: 🔹 Separation of responsibility: Each domain Twin module (Geology, Planning, Processing, etc.) manages its specific domain while maintaining strict engineering precision. 🔹 Verification layer: Validating calculations for independence, compliance with mass and metal balances, and operating within established tolerances. 🔹 Change management: Any operational scenario—from a schedule revision to a blend adjustment—must pass through criticality gates (K1–K4) and rights gates. We are not promising "autonomous control". We propose an architecture where the AI algorithm serves strictly as a tool that generates an evidence-backed recommendation, while the final decision and accountability remain with the human engineer. This material is methodological in nature and establishes the standard for the entire upcoming series of publications. I welcome your professional feedback, comments, and critique. Volume I (Geology Twin) is coming soon.
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Durmishkhan Gakharia (2026) studied this question.
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