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Determination of Truck–Shovel Configuration of Open-Pit Mine: A Simulation Method Based on Mathematical Model

Author

Listed:
  • Yuhao Zhang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Ziyu Zhao

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Lin Bi

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China
    Changsha Digital Mine Co., Ltd., Changsha 410221, China)

  • Liming Wang

    (School of Resources and Safety Engineering, Central South University, Changsha 410083, China)

  • Qing Gu

    (School of Mechanic Engineering, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

The truck–shovel system is the most common material transportation system in open-pit mines. The configuration of trucks and shovels directly affects the efficiency and cost of transportation in open-pit mines. Under the condition that the types and quantities of trucks and shovels are known, in order to obtain the optimal configuration scheme in the open-pit mine transportation system this paper presents a method to determine the optimal scheme by conducting experiments based on the simulation truck–shovel system model in Flexsim software. We test candidate configuration schemes that are solved by the mathematical model with daily minimum production and expected profit constraints in the simulation model, and finally obtain the optimal truck–shovel configuration scheme that meets the ore output requirements of each loading point. Through simulation experiments, the daily production of the optimal truck–shovel configuration scheme is 3.75% higher than that of the original mine scheme and the profit is increased by 3.85%. The results show that the open-pit truck–shovel system constructed by Flexsim has great research potential and value for the optimization of truck–shovel configuration schemes.

Suggested Citation

  • Yuhao Zhang & Ziyu Zhao & Lin Bi & Liming Wang & Qing Gu, 2022. "Determination of Truck–Shovel Configuration of Open-Pit Mine: A Simulation Method Based on Mathematical Model," Sustainability, MDPI, vol. 14(19), pages 1-22, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12338-:d:927832
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    References listed on IDEAS

    as
    1. Ta, Chung H. & Ingolfsson, Armann & Doucette, John, 2013. "A linear model for surface mining haul truck allocation incorporating shovel idle probabilities," European Journal of Operational Research, Elsevier, vol. 231(3), pages 770-778.
    2. Magdalena Rozmus & Jarosław Tokarczyk & Dariusz Michalak & Marek Dudek & Kamil Szewerda & Marek Rotkegel & Aleš Lamot & Janez Rošer, 2021. "Application of 3D Scanning, Computer Simulations and Virtual Reality in the Redesigning Process of Selected Areas of Underground Transportation Routes in Coal Mining Industry," Energies, MDPI, vol. 14(9), pages 1-21, May.
    3. Chaowasakoo, Patarawan & Seppälä, Heikki & Koivo, Heikki & Zhou, Quan, 2017. "Improving fleet management in mines: The benefit of heterogeneous match factor," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1052-1065.
    4. Xiaoqiang Zhang & Yuanyuan Pan, 2022. "Preparation, Properties and Application of Gel Materials for Coal Gangue Control," Energies, MDPI, vol. 15(2), pages 1-15, January.
    5. Christina N. Burt & Lou Caccetta, 2014. "Equipment Selection for Surface Mining: A Review," Interfaces, INFORMS, vol. 44(2), pages 143-162, April.
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