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Intelligent Scheduling for Underground Mobile Mining Equipment
Department of Civil and Environmental Engineering, School of Engineering, Aalto.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
Department of Civil and Environmental Engineering, School of Engineering, Aalto.
School of Civil, Environmental and Mining Engineering, University of Adelaide.
2015 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 10, no 6, article id e0131003Article in journal (Refereed) Published
Abstract [en]

Many studies have been carried out and many commercial software applications have been developed to improve the performances of surface mining operations, especially for the loader-trucks cycle of surface mining. However, there have been quite few studies aiming to improve the mining process of underground mines. In underground mines, mobile mining equipment is mostly scheduled instinctively, without theoretical support for these decisions. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions to reschedule and to adapt the changes. This investigation first introduces the motivation, the technical background, and then the objective of the study. A decision support instrument (i.e. schedule optimizer for mobile mining equipment) is proposed and described to address this issue. The method and related algorithms which are used in this instrument are presented and discussed. The proposed method was tested by using a real case of Kittilä mine located in Finland. The result suggests that the proposed method can considerably improve the working efficiency and reduce the working time of the underground mine

Place, publisher, year, edition, pages
2015. Vol. 10, no 6, article id e0131003
National Category
Other Civil Engineering
Research subject
Mining and Rock Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-9699DOI: 10.1371/journal.pone.0131003ISI: 000356835800130PubMedID: 26098934Scopus ID: 2-s2.0-84939140296Local ID: 85e984cf-7ee9-46a5-8c91-881f3723b969OAI: oai:DiVA.org:ltu-9699DiVA, id: diva2:982637
Note
Validerad; 2015; Nivå 2; 20150629 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Schunnesson, Håkan

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