Intelligent Scheduling for Underground Mobile Mining Equipment

Zhen Song, Håkan Schunnesson, Mikael Rinne, John Sturgul

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)
158 Downloads (Pure)


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.
Original languageEnglish
Article numbere0131003
Pages (from-to)1-21
JournalPloS one
Issue number6
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed


  • mining
  • mobile
  • optimize
  • scheduling
  • underground


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