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Development of a Markov model for production performance optimisation: Application for semi-automatic and manual LHD machines in underground mines
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0002-5347-0853
Mechanical Engineering, University of Alberta, Edmonton.
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, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-4107-0991
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2014 (English)In: International Journal of Mining, Reclamation and Environment, ISSN 1748-0930, E-ISSN 1748-0949, Vol. 28, no 5, p. 342-355Article in journal (Refereed) Published
Abstract [en]

This paper compares three ways to operate a load haul dump (LHD) machine, manual operation, automatic operation (fleet operation) and semi-automatic operation, to find the best operating mode. In a fault tree analysis, different failures are classified and analysed, but the way to recover from certain states is not accounted for, which is something a Markov model can handle. The paper is based on the analysis of real data from an underground mine. A Markov model has been built for mining application and it is shown that a semi-automatic LHD has the highest probability of being in a productive state since it has the advantage of changing operating modes (manual and automatic) depending on the need and situation. Hence, the semi-automatic LHD is the best choice from an operational point of view. The paper fills a gap in the literature on manual vs. automatically operated LHDs by providing a new way of evaluating the operating mode of LHDs using Markov modelling, while considering the operating environment.

Place, publisher, year, edition, pages
2014. Vol. 28, no 5, p. 342-355
National Category
Other Civil Engineering
Research subject
Mining and Rock Engineering; Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-3110DOI: 10.1080/17480930.2013.862026ISI: 000343814000008Scopus ID: 2-s2.0-84908499794Local ID: 0e504339-ede6-4d9f-a9ca-0e6de93112fdOAI: oai:DiVA.org:ltu-3110DiVA, id: diva2:975966
Note
Validerad; 2014; 20140815 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Gustafson, AnnaSchunnesson, HåkanGalar, DiegoKumar, Uday

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