Integration of simulation and dispatch modelling to predict fleet productivity: an open-pit mining case
Predicting the fleet requirement based on fleet productivity estimation is one of the critical parts of a robust long-term mine plan. The dispatch logic that determines the return destination of the empty trucks is significantly important in the overall full and empty travel distances and trucks...
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| Published in | Mining technology (2018) Vol. 131; no. 2; pp. 67 - 79 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London, England
Taylor & Francis
01.06.2022
SAGE Publications |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2572-6668 2572-6676 |
| DOI | 10.1080/25726668.2021.2001255 |
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| Abstract | Predicting the fleet requirement based on fleet productivity estimation is one of the critical parts of a robust long-term mine plan. The dispatch logic that determines the return destination of the empty trucks is significantly important in the overall full and empty travel distances and trucks' productivity. In this paper, a Monte-Carlo simulation model is presented to mimic the real truck-and-shovel operations and measure trucks' productivity in terms of Tonne Per Gross Operating Hour (TPGOH). A linear programming model is integrated into the simulation model to optimize the dispatch decision through distance minimization subject to the mine's production schedule. The historical data records of oil sands mining operations are used to validate model's performance. The results show significant improvement over the existing mine site's method with closely matching the real TPGOH and better estimation of the total empty travel distance, as a result of new dispatch model implementation. |
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| AbstractList | Predicting the fleet requirement based on fleet productivity estimation is one of the critical parts of a robust long-term mine plan. The dispatch logic that determines the return destination of the empty trucks is significantly important in the overall full and empty travel distances and trucks' productivity. In this paper, a Monte-Carlo simulation model is presented to mimic the real truck-and-shovel operations and measure trucks' productivity in terms of Tonne Per Gross Operating Hour (TPGOH). A linear programming model is integrated into the simulation model to optimize the dispatch decision through distance minimization subject to the mine's production schedule. The historical data records of oil sands mining operations are used to validate model's performance. The results show significant improvement over the existing mine site's method with closely matching the real TPGOH and better estimation of the total empty travel distance, as a result of new dispatch model implementation. |
| Author | Badiozamani, Mahdi Moradi-Afrapoli, Ali Yeganejou, Mojtaba Askari-Nasab, Hooman |
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| ContentType | Journal Article |
| Copyright | 2021 Institute of Materials, Minerals and Mining and The AusIMM Published by Taylor & Francis on behalf of the Institute and The AusIMM 2021 2021 Institute of Materials, Minerals and Mining and The AusIMM Published by Taylor & Francis on behalf of the Institute and The AusIMM |
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| SubjectTerms | Dispatch modelling fleet productivity Monte Carlo simulation truck requirement |
| Title | Integration of simulation and dispatch modelling to predict fleet productivity: an open-pit mining case |
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