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Conceptual models for mining at greater depths: Automated bolt rigs and scaling rigs
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0002-5347-0853
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0002-2306-9241
Number of Authors: 42016 (English)Manuscript (preprint) (Other academic)
Abstract [en]

One of the challenges that underground mines face today is the deepening of the mines. This, together with lower grades of the deposits, makes the mines strive for higher productivity and lower costs. By introducing autonomous vehicles, the operators will be removed from the face, and thus safety for operators will be improved. Since autonomous vehicles are scheduled to operate during breaks, there is a potential for a productivity increase. The goal with this study was to determine if and to which degree autonomous bolt rigs and scaling rigs can improve the productivity in a deep underground mine.The research is based on data collected during 2013 from New Boliden AB’s Kristineberg mine in Sweden. A simulation tool, SimMine, was used for analyzing the effects of operational changes and for simulation of parameters that are difficult to estimate, such as traffic congestions. A number of scenarios were simulated and compared to the base case with focus on productivity.It can be concluded that the simulation scenarios using faster, manually operated vehicles shows a productivity increase, and that the automated vehicles further improved the productivity increase. The largest productivity increase comes however from faster vehicles, and not from the automation itself.

Place, publisher, year, edition, pages
2016.
National Category
Other Civil Engineering
Research subject
Mining and Rock Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-23439Local ID: 6f9c857a-472c-405b-8fb2-fc9c3891a761ISBN: 978-91-7583-519-8 (electronic)OAI: oai:DiVA.org:ltu-23439DiVA, id: diva2:996488
Note

Upprättat; 2016; 20160129 (anngus)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-04-16

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Gustafson, AnnaSundqvist, FredrikSjödin, ErikGreberg, Jenny

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  • apa
  • harvard1
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  • Other locale
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Output format
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