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Underground production scheduling with ventilation and refrigeration considerations

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Abstract

Underground mine production scheduling determines when, if ever, activities associated with the extraction of ore should be executed. The accumulation of heat in the mine where operators are working is a major concern. At the time of this writing, production scheduling and ventilation decisions are not made in concert. Correspondingly, heat limitations are largely ignored. Our mixed-integer program maximizes net present value subject to constraints on precedence, and mill and extraction capacities with the consideration of heat using thermodynamic principles, while affording the option of activating refrigeration to mitigate heat accumulation. In seconds to hours, depending on the problem size (up to thousands of activities and 900 daily time periods), a corresponding methodology that exploits the mathematical problem structure provides schedules that maintain a safe working environment for mine operators; optimality gaps are no more than 15% and average less than half that for otherwise-intractable instances.

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References

  • Acuña EI, Lowndes IS (2014) A review of primary mine ventilation system optimization. Interfaces 44(2):163–175

    Article  Google Scholar 

  • Adwo (2020) Mining truck driving out of underground mine [digital image]. Shutterstock, Accessed: 03/10/2021

  • Agnor M (2017) Gold mining underground [digital image]. Shutterstock, Accessed: 03/10/2021

  • Anderson J, Longson I (1986) Optimisation of ventilation and refrigeration in British coal mines. Min Eng 146:115–20

    Google Scholar 

  • Atlas Copco (2007) Mining methods in underground mining. Stockholm: Atlas Copco

  • Bascompta M, Castañón AM, Sanmiquel L, Oliva J (2016) Heat flow assessment in an underground mine: an approach to improve the environmental conditions. Dyna 83(197):174–179

    Google Scholar 

  • Bienstock D, Zuckerberg M (2010) Solving LP relaxations of large-scale precedence constrained problems. In: International Conference on Integer Programming and Combinatorial Optimization, Springer, pp 1–14

  • Both C, Dimitrakopoulos R (2020) Joint stochastic short-term production scheduling and fleet management optimization for mining complexes. Optim Eng, pp 1–27

  • Brake DJ, Fulker R (2000) The ventilation and refrigeration design for Australia’s deepest and hottest underground operation: the Enterprise mine. Proc MassMin, pp 611–621

  • Brickey AJ (2015) Underground production scheduling optimization with ventilation constraints. PhD thesis, Colorado School of Mines. Arthur Lakes Library

  • Campeau LP, Gamache M (2020) Short-term planning optimization model for underground mines. Comput Op Res 115:104642

    Article  MathSciNet  MATH  Google Scholar 

  • Carlyle M, Eaves C (2001) Underground planning at stillwater mining company. Interfaces 31(4):50–60

    Article  Google Scholar 

  • Carpentier S, Gamache M, Dimitrakopoulos R (2016) Underground long-term mine production scheduling with integrated geological risk management. Min Technol 125(2):93–102

    Article  Google Scholar 

  • Chowdu A, Nesbitt P, Brickey A, Newman A (2021) Operations research in underground mine planning: A review. INFORMS Journal on Applied Analytics, accepted

  • De Souza E (2007) Optimization of complex mine ventilation systems with computer network modelling. IFAC Proceedings Volumes 40(11):323–329, https://doi.org/10.3182/20070821-3-CA-2919.00049, URL https://www.sciencedirect.com/science/article/pii/S1474667015315597, 12th IFAC Symposium on Automation in Mining, Mineral and Metal Processing

  • Deswik Mining Consultants (Australia) Pty Ltd (2018) Deswik.CAD

  • Dimitrakopoulos R, Grieco N (2009) Stope design and geological uncertainty: quantification of risk in conventional designs and a probabilistic alternative. J Min Sci 45(2):152–163

    Article  Google Scholar 

  • Dirkx R, Kazakidis V, Dimitrakopoulos R (2019) Stochastic optimisation of long-term block cave scheduling with hang-up and grade uncertainty. Int J Min, Reclam Environ 33(6):371–388

    Article  Google Scholar 

  • Donoghue A (2004) Occupational health hazards in mining: an overview. Occup Med 54(5):283–289

    Article  Google Scholar 

  • Gamma Technologies (2017) GT-Power user’s manual, GT-Suite version 2017. Gamma Technologies

  • Gertsch RE, Bullock RL (1998) Techniques in underground mining: selections from underground mining methods Handbook. Society for Mining Metallurgy and Exploration, Littleton

    Google Scholar 

  • Greth A, Roghanchi P, Kocsis K (2017) A review of cooling system practices and their applicability to deep and hot underground U.S. mines. In: Proceedings of the 16th North American Mine Ventilation Symposium, Golden, CO, USA, pp 17–22

  • Hamrin H (1980) Guide to underground mining: methods and applications. Atlas Copco, Sweden

    Google Scholar 

  • Hartman HL, Mutmansky JM (2002) Introductory Mining Engineering. Wiley, Hoboken

    Google Scholar 

  • Hartman HL, Mutmansky JM, Ramani RV, Wang YJ (2012) Mine Ventilation and Air Conditioning. Wiley, Hoboken

    Google Scholar 

  • Howes M (2011) Ventilation and cooling in underground mines. Min Quarr 74:45–46

    Google Scholar 

  • Huang S, Li G, Ben-Awuah E, Afum BO, Hu N (2020a) A robust mixed integer linear programming framework for underground cut-and-fill mining production scheduling. Int J Min, Reclam Environ 34(6):397–414

    Article  Google Scholar 

  • Huang S, Li G, Ben-Awuah E, Afum BO, Hu N (2020b) A stochastic mixed integer programming framework for underground mining production scheduling optimization considering grade uncertainty. IEEE Access 8:24495–24505

    Article  Google Scholar 

  • Hustrulid WA, Bullock RC (2001) Underground mining methods: engineering fundamentals and international case studies. Society for Mining Metallurgy and Exploration, Littleton

    Google Scholar 

  • ILOG IBM (2019) CPLEX optimizer 12.9

  • Jewbali J, Wang H, Johnson C (2015) Resource model uncertainty analysis and stope optimizer (MSO) evaluation for an underground metal mine project. In Application of Computers and Operations Research in the Mineral Industry. Society for Mining Metallurgy and Exploration, Littleton

    Google Scholar 

  • Johnson TB (1968) Optimum open pit mine production scheduling. Tech. rep., DTIC Document

  • Khodayari F, Pourrahimian Y (2019) Long-term production scheduling optimization and 3D material mixing analysis for block caving mines. Min Technol 128(2):65–76

    Article  Google Scholar 

  • Kuchta M, Newman A, Topal E (2004) Implementing a production schedule at LKAB’s Kiruna mine. Interfaces 34(2):124–134

    Article  Google Scholar 

  • Kutcha M, Newman AM, Topal E (2003) Production scheduling at LKAB’s Kiruna mine using mixed-integer programming. Min Eng 55(4):35–40

    Google Scholar 

  • Lambert B, Brickey A, Newman A, Eurek K (2014) Open-pit block-sequencing formulations: a tutorial. Interfaces 44(2):127–142

    Article  Google Scholar 

  • Larson M (2021) private communication

  • Lazaro P, Momayez M (2020) Development of a modified predicted heat strain model for hot work environments. Int J Min Sci Tech 30(4):477–481

    Article  Google Scholar 

  • Lerchs H, Grossmann IF (1965) Optimum design of open-pit mines. Trans CIM 58:47–54

    Google Scholar 

  • Lopes TVF (2017) Underground mine production scheduling using OMP solver: Analysis of modifications to an integer programming model and implementation of a sliding time window heuristic. Master’s thesis, South Dakota School of Mines and Technology, Rapid City

  • Magri E, Unsted A (1976) Mine production, ventilation and refrigeration planning-a unified approach via mathematical programming. International Federation of Automatic Control Proceedings Volumes 9(5):91–104

  • Marks JR (1980) Refrigeration economics at the Star mine. In Proceedings second international mine ventilation congress, SME, Littleton, CO, pp 649–655

  • Martinez M, Newman AM (2011) Using decomposition to optimize long- and short-term production scheduling at LKAB’s Kiruna Mine. Euro J Op Res 211(1):184–197

    Article  MATH  Google Scholar 

  • Matamoros MEV, Dimitrakopoulos R (2016) Stochastic short-term mine production schedule accounting for fleet allocation, operational considerations and blending restrictions. Euro J Op Res 255(3):911–921

    Article  MathSciNet  MATH  Google Scholar 

  • McPherson MJ (2009) Subsurface ventilation engineering. Mine Ventilation Services Inc., USA

    Google Scholar 

  • McPherson MJ (2012) Subsurface ventilation and environmental engineering. Springer, Berlin

    Google Scholar 

  • Mohtasham M, Mirzaei-Nasirabad H, Alizadeh B (2021) Optimization of truck-shovel allocation in open-pit mines under uncertainty: a chance-constrained goal programming approach. Min Techn 130(2): 81–100

    Article  Google Scholar 

  • Muñoz G (2012) Modelos de optimización lineal entera y aplicaciones a la minería. Master’s thesis, Dept. Math. Engineering, Universidad de Chile, Santiago, Chile

  • Myers P, Standing C, Collier P, Noppe M (2005) Assessing underground mining potential at Ernest Henry Mine, using conditional simulation and stope optimisation. Orebody Model Strateg Mine Plan, Spectr Ser 14:141–180

    Google Scholar 

  • Nehring M, Topal E, Kizil M, Knights P (2010) An investigation to integrate optimum long-term planning with short planning in underground mine production scheduling. In: Mine Planning and Equipment Selection Conference, Fremantle, Western Australia, pp 1–13

  • Nehring M, Topal E, Kizil M, Knights P (2012) Integrated short-and medium-term underground mine production scheduling. J South Afr Inst Min Metal 112(5):365–378

    Google Scholar 

  • Nesbitt P, Blake LR, Lamas P, Goycoolea M, Pagnoncelli BK, Newman A, Brickey A (2021) Underground mine scheduling under uncertainty. Eur J Oper Res 294(1):340–352

    Article  MATH  Google Scholar 

  • Newman A, Kuchta M (2007) Using aggregation to optimize long-term production planning at an underground mine. Euro J Op Res 176(2):1205–1218

    Article  MATH  Google Scholar 

  • Newman A, Rubio E, Caro R, Weintraub A, Eurek K (2010) A review of operations research in mine planning. Interfaces 40(3):222–245

    Article  Google Scholar 

  • Nichols S, Bogin G, Newman A (2019) Simulation of the impact of environmental conditions in underground mines on truck and loader engine efficiency and emissions. In: SME Annual Conference & Expo and CMA 121st National Western Mining Conference, SME, pp 716–721

  • Nieto A (2011) Key deposit indicators (KDI) and key mining method indicators (KMI) in underground mining method selection. Trans Soc Min, Metal Eng 328:381–396

    Google Scholar 

  • O’Sullivan D, Newman AM (2014) Extraction and backfill scheduling in a complex underground mine. Interfaces 44(2):204–221

    Article  Google Scholar 

  • O’Sullivan D, Brickey A, Newman A (2015) Is open pit production scheduling ‘easier’ than its underground counterpart? Min Eng 67(4):68–73

    Google Scholar 

  • Rivera O, Brickey AJ, Espinoza D, Goycoolea M, Moreno E (2016) The OMP guide. In: Technical Report, Universidad Adolfo Ibañez

  • Rivera Letelier O, Espinoza D, Goycoolea M, Moreno E, Muñoz G (2020) Production scheduling for strategic open pit mine planning: a mixed-integer programming approach. Op Res 68(5):1425–1444

    Article  MathSciNet  MATH  Google Scholar 

  • Sebutsoe T, Musingwini C (2017) Characterizing a mining production system for decision-making purposes in a platinum mine. J South Afr Inst Min Metal 117(2):199–206

    Article  Google Scholar 

  • Sharma V (2015) Longterm schedule optimization of an underground mine under geotechnical and ventilation constraints using SOT. PhD thesis, Laurentian University of Sudbury

  • Smith M, Sheppard I, Karunatillake G (2003) Using MIP for strategic life-of-mine planning of the lead/zinc stream at Mount Isa mines. In: Proceedings of the 31st International APCOM Symposium, Cape Town, South Africa, pp 465–474

  • Sotoudeh F, Nehring M, Kizil M, Knights P, Mousavi A (2020) Production scheduling optimisation for sublevel stoping mines using mathematical programming: a review of literature and future directions. Resour Policy 68:101809

    Article  Google Scholar 

  • Tavchandjian O, Proulx A, Anderson M (2018) Application of conditional simulations to capital decisions for Ni-sulfide and Ni-laterite deposits. In: Advances in Applied Strategic Mine Planning, Springer, pp 319–333

  • Trout L (1995) Underground mine production scheduling using mixed integer programming. In: 25th International APCOM Symposium Proceedings, pp 395–400

  • Wagner H (2013) The management of heat flow in deep mines. Min Rep 149(2):88–100

    Article  Google Scholar 

  • Zhang H, Hauta R, Fava L (2017) Mine schedule optimisation with ventilation constraints: a case study. In: Proceedings of the First International Conference on Underground Mining Technology, Australian Centre for Geomechanics, pp 145–152

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Acknowledgements

We acknowledge our industry partners who provided data, funding and an explanation of the scheduling problem. We thank Professor Marcos Goycoolea from the University of Adolfo Ibañez; Samuel Nichols, Kieran Lewis, Eric Smoorenberg, John Ayaburi, and Aditya Juganda from the Colorado School of Mines; and Akshay Chowdu from the South Dakota School of Mines for providing additional insights regarding model formulation. We also thank Dr. Mark Larson and Mr. Donovan Benton from the National Institute of Occupational Safety and Health for their constructive comments. This research has been partially funded by the National Institute of Occupational Safety and Health as part of the Mine Ventilation and Safety Research and Capacity Building program, contract number: 0000HCCS-2019-36404, and by the National Agency for Research and Development (ANID), Chile, Scholarship Program, Becas de Doctorado Nacional: 2017-21180460.

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Ogunmodede, O., Lamas, P., Brickey, A. et al. Underground production scheduling with ventilation and refrigeration considerations. Optim Eng 23, 1677–1705 (2022). https://doi.org/10.1007/s11081-021-09682-4

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