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Underground mine scheduling modelled as a flow shop: a review of relevant work and future challenges
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. ABB Corp Res, Control Optimizat & Analyt, Automat Solut, Vasteras, Sweden..
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
Lulea Univ Technol, Dept Civil Environm & Nat Resources Engn, Div Min & Geotech Engn, Lulea, Sweden..
2018 (English)In: The Southern African Journal of Mining and Metallurgy, ISSN 2225-6253, E-ISSN 1543-9518, Vol. 118, no 12, p. 1265-1276Article, review/survey (Refereed) Published
Abstract [en]

Advanced planning and automation are increasingly important in modern mines. Sophisticated methods for long-term mine planning are often used, and the advent of autonomous machines makes the actual operation more predictable. However, the interface between these two timescales, i.e. the scheduling of the mobile production fleet, often limits the ability to operate mines at maximum profitability. We show how scheduling the production fleet in an underground mine can be modelled as a flow shop. A flow shop is a general abstract process formulation that captures the key properties of a scheduling problem without going into specific details. Thus, the flow shop enables mine scheduling to reap the benefits of scheduling research from other industries. We review recent results from the mining community and the flow shop community, and introduce scheduling methods used in these two fields. This work aims at providing value to researchers from the mining community who want to leverage their skill set, as well as to theoretical researchers by presenting the mining process as a potential application area. Lastly, we discuss the results, and outline some future challenges and opportunities facing the industry.

Place, publisher, year, edition, pages
SOUTHERN AFRICAN INST MINING METALLURGY , 2018. Vol. 118, no 12, p. 1265-1276
Keywords [en]
underground mining, scheduling, flow shop, optimization
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-241017DOI: 10.17159/2411-9717/2018/v118n12a5ISI: 000453404400005OAI: oai:DiVA.org:kth-241017DiVA, id: diva2:1276438
Funder
Wallenberg Foundations
Note

QC 20190108

Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-08-20Bibliographically approved

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Åstrand, MaxJohansson, Mikael

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