Deterministic Optimization for Short-Term Scheduling of Thin Seam Deposits With Autonomous Technologies
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PublisherThe University of Arizona.
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AbstractThe extraction of thin seam mineral deposits requires to overcome several challenges due to the level of accuracy needed in order to cut layers of reduced thickness, which has a direct impact on the reserves, dilution control, and blending, therefore in the final economic results of the operation. This becomes more critical when seams are less than 40 cm. thick. A strategy based on the deployment of smart equipment, which includes autonomous Scrapers coupled with high precision Continuous Surfer Mining (CSM) machines, drones for surveying, and modern programming tools, provides a range of multiple scenarios of scheduled sequences, tailored to satisfying Processing Plant requirements. This proposed combination increases the reserve, diminishes the dilution, and improves the long-term present value of the mine. Case studies are presented with a test of the production system, a schedule algorithm, a short-term sequence code in Python, and the results for optimization using actual field data.
Degree ProgramGraduate College
Mining, Geological & Geophysical Engineering