A Deviation-Minimization Approach to Short-Term Underground Mine Schedule Optimization [2023]
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2023/10/01
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English
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Description:Production forecasts derived from the medium-term schedule represent the best path forward for underground mining operations to achieve corporate and operational goals. Unforeseen circumstances, such as equipment breakdown, can cause significant deviations from established production forecasts in the short term. Such situations require timely mitigation of the effects of the deviations in order to stay as close as possible to the medium-term plan. This paper presents a deterministic mathematical formulation for short-term scheduling that addresses this challenge. The formulation is able to make up for deficits resulting from operational disruptions by minimizing deviations from medium-term production goals and medium-term activity start dates. We demonstrate this in a case study by simulating disruptions involving reduction in ore extraction capacity and development advance rate. Aside from the rescheduling capability, this formulation can help mine planners conduct analysis on the impact of various disruptions on the schedule. The formulation can help identify those conditions or disruptions that are more detrimental to the achievement of forecast targets, or otherwise. The formulation also affords mine planners the flexibility to prioritize one production goal over the other, depending on operational conditions at the mine. In the future, we seek to incorporate in the formulation respirable dust, diesel particulate matter, and ventilation constraints in order to create more realistic schedules and enhance miners' health and safety. [Description provided by NIOSH]
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ISSN:2524-3462
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Volume:40
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Issue:5
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NIOSHTIC Number:nn:20068604
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Citation:Min Metall Explor 2023 Oct; 40(5):1749-1765
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Email:andrea.brickey@sdsmt.edu
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Federal Fiscal Year:2024
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Peer Reviewed:True
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Main Document Checksum:urn:sha-512:5211fcf73dfe510b830ed1a4020c198fb73a6ca1012591a381e9ca5870ff6f5fcf4f0d0474f2c9fcbcf66a8bf84a024f2fb259559d20f91c7b796edf78a53939
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