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Intelligent Scheduling for Underground Mobile Mining Equipment.

Song Z, Schunnesson H, Rinne M, Sturgul J - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil and Environmental Engineering, School of Engineering, Aalto University, Espoo, Finland.

ABSTRACT
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.

No MeSH data available.


Cross section of Kittilä underground mine [24].
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pone.0131003.g014: Cross section of Kittilä underground mine [24].

Mentions: Kittilä mine is an underground gold mine located at Lapland, Finland. This mine is owned by Agnico Eagle Mine Limited. It started its mine production on 1 May 2009. The mine produces around 3,000 tonnes of ore per day, and it is targeted to produce 4,300 kilograms of gold in 2014. After this, the average production will be roughly around 4,700 kilograms of gold per year in 2015 to 2016. Originally Kittilä mine started as two open pits which are called Suuri and Roura. The underground mine started in October 2010. All of the open pits had already been mined out by November 2012. Now, only the underground mining exists. (Fig 14) The broken ore is hauled by truck to the surface and dumped at ore stockpile. The stockpile will feed the crusher which is next to the processing plant.


Intelligent Scheduling for Underground Mobile Mining Equipment.

Song Z, Schunnesson H, Rinne M, Sturgul J - PLoS ONE (2015)

Cross section of Kittilä underground mine [24].
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4476722&req=5

pone.0131003.g014: Cross section of Kittilä underground mine [24].
Mentions: Kittilä mine is an underground gold mine located at Lapland, Finland. This mine is owned by Agnico Eagle Mine Limited. It started its mine production on 1 May 2009. The mine produces around 3,000 tonnes of ore per day, and it is targeted to produce 4,300 kilograms of gold in 2014. After this, the average production will be roughly around 4,700 kilograms of gold per year in 2015 to 2016. Originally Kittilä mine started as two open pits which are called Suuri and Roura. The underground mine started in October 2010. All of the open pits had already been mined out by November 2012. Now, only the underground mining exists. (Fig 14) The broken ore is hauled by truck to the surface and dumped at ore stockpile. The stockpile will feed the crusher which is next to the processing plant.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Civil and Environmental Engineering, School of Engineering, Aalto University, Espoo, Finland.

ABSTRACT
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.

No MeSH data available.