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dc.contributor.advisorTenorio, Victor
dc.contributor.authorPalomino, Orlando
dc.creatorPalomino, Orlando
dc.date.accessioned2021-07-19T20:51:46Z
dc.date.available2021-07-19T20:51:46Z
dc.date.issued2021
dc.identifier.citationPalomino, Orlando. (2021). Deterministic Optimization for Short-Term Scheduling of Thin Seam Deposits With Autonomous Technologies (Master's thesis, University of Arizona, Tucson, USA).
dc.identifier.urihttp://hdl.handle.net/10150/660773
dc.description.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.
dc.language.isoen
dc.publisherThe University of Arizona.
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectContinuous Surface Miner
dc.subjectMining
dc.subjectPython for Mining
dc.subjectScrapers
dc.subjectSeam Deposits
dc.subjectShort-term Mining Plan
dc.titleDeterministic Optimization for Short-Term Scheduling of Thin Seam Deposits With Autonomous Technologies
dc.typetext
dc.typeElectronic Thesis
thesis.degree.grantorUniversity of Arizona
thesis.degree.levelmasters
dc.contributor.committeememberKemeny, John
dc.contributor.committeememberMomayez, Moe
dc.contributor.committeememberVivas, Raul Ernesto
thesis.degree.disciplineGraduate College
thesis.degree.disciplineMining, Geological & Geophysical Engineering
thesis.degree.nameM.S.
refterms.dateFOA2021-07-19T20:51:46Z


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