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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.


Time delay impacts for typical excavation practices with drilling and blasting [8].
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pone.0131003.g001: Time delay impacts for typical excavation practices with drilling and blasting [8].

Mentions: However, there have not been relevant studies that cover the entire mining process of underground mining. Normally, underground mining operations are much more complicated and diverse compared with surface mining. The difference is mainly caused by mining methods, and the complexity is due to additional constraints required for underground mining. In underground mining operations, mobile mining machines are mostly scheduled instinctively, without theoretical support for these decisions. It can cause less confidence for miners and less efficient operations. Additionally, foremen in each shift may change the schedule based on their own experiences, if they do not agree with the existing schedule. It is difficult to keep the operations consistent. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions for a new schedule and to adjust the operations. Therefore, there is a need to develop a decision support instrument which can help miners to initiate the schedule of mobile mining equipment, and rapidly reschedule these machines when unexpected events occur. Fig 1 shows that scheduling (incl. re-scheduling) can be a considerable part (more than 10%) of total working time, even in modern mines, such as Falconbridge and Boliden.


Intelligent Scheduling for Underground Mobile Mining Equipment.

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

Time delay impacts for typical excavation practices with drilling and blasting [8].
© Copyright Policy
Related In: Results  -  Collection

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

pone.0131003.g001: Time delay impacts for typical excavation practices with drilling and blasting [8].
Mentions: However, there have not been relevant studies that cover the entire mining process of underground mining. Normally, underground mining operations are much more complicated and diverse compared with surface mining. The difference is mainly caused by mining methods, and the complexity is due to additional constraints required for underground mining. In underground mining operations, mobile mining machines are mostly scheduled instinctively, without theoretical support for these decisions. It can cause less confidence for miners and less efficient operations. Additionally, foremen in each shift may change the schedule based on their own experiences, if they do not agree with the existing schedule. It is difficult to keep the operations consistent. Furthermore, in case of unexpected events, it is hard for miners to rapidly find solutions for a new schedule and to adjust the operations. Therefore, there is a need to develop a decision support instrument which can help miners to initiate the schedule of mobile mining equipment, and rapidly reschedule these machines when unexpected events occur. Fig 1 shows that scheduling (incl. re-scheduling) can be a considerable part (more than 10%) of total working time, even in modern mines, such as Falconbridge and Boliden.

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.