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Implementing a Production Schedule at LKAB's Kiruna Mine

Author

Listed:
  • Mark Kuchta

    (Mining Engineering Department, Colorado School of Mines, 1500 Illinois Street, Golden, Colorado 80401)

  • Alexandra Newman

    (Division of Economics and Business, Colorado School of Mines, 1500 Illinois Street, Golden, Colorado 80401)

  • Erkan Topal

    (Mining Engineering Department, Dicle University, Diybakir, Turkey)

Abstract

LKAB's Kiruna Mine, located in northern Sweden, produces about 24 million tons of iron ore yearly using an underground mining method known as sublevel caving. To efficiently run the mills that process the iron ore, the mine must deliver planned quantities of three ore types. We used mixed-integer programming to schedule Kiruna's operations, specifically, which production blocks to mine and when to mine them to minimize deviations from monthly planned production quantities while adhering to operational restrictions. These production schedules save costs compared to schedules produced manually by meeting desired production quantities more closely and reducing employee time spent on preparing schedules.

Suggested Citation

  • Mark Kuchta & Alexandra Newman & Erkan Topal, 2004. "Implementing a Production Schedule at LKAB's Kiruna Mine," Interfaces, INFORMS, vol. 34(2), pages 124-134, April.
    • Handle: RePEc:inm:orinte:v:34:y:2004:i:2:p:124-134
    DOI: 10.1287/inte.1030.0059
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    References listed on IDEAS

    as
    1. W. Matthew Carlyle & B. Curtis Eaves, 2001. "Underground Planning at Stillwater Mining Company," Interfaces, INFORMS, vol. 31(4), pages 50-60, August.
    2. Underwood, Robert & Tolwinski, Boleslaw, 1998. "A mathematical programming viewpoint for solving the ultimate pit problem," European Journal of Operational Research, Elsevier, vol. 107(1), pages 96-107, May.
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    Citations

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    Cited by:

    1. Sotoudeh, Farzad & Nehring, Micah & Kizil, Mehmet & Knights, Peter & Mousavi, Amin, 2020. "Production scheduling optimisation for sublevel stoping mines using mathematical programming: A review of literature and future directions," Resources Policy, Elsevier, vol. 68(C).
    2. Furtado e Faria, Matheus & Dimitrakopoulos, Roussos & Lopes Pinto, Cláudio Lúcio, 2022. "Integrated stochastic optimization of stope design and long-term underground mine production scheduling," Resources Policy, Elsevier, vol. 78(C).
    3. Chung, Joyce & Asad, Mohammad Waqar Ali & Topal, Erkan, 2022. "Timing of transition from open-pit to underground mining: A simultaneous optimisation model for open-pit and underground mine production schedules," Resources Policy, Elsevier, vol. 77(C).
    4. Chimunhu, Prosper & Topal, Erkan & Ajak, Ajak Duany & Asad, Waqar, 2022. "A review of machine learning applications for underground mine planning and scheduling," Resources Policy, Elsevier, vol. 77(C).
    5. Foroughi, Sorayya & Hamidi, Jafar Khademi & Monjezi, Masoud & Nehring, Micah, 2019. "The integrated optimization of underground stope layout designing and production scheduling incorporating a non-dominated sorting genetic algorithm (NSGA-II)," Resources Policy, Elsevier, vol. 63(C), pages 1-1.

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