Introducing an Approach to Control Caving Direction in Block Caving Mining

Document Type : Research - Paper

Authors

Assistant Professor, Dept. of Mining Engineering, Urmia University, Urmia, Iran

Abstract

Mass production and the high rate of block caving have caused to special considerations in operational optimization of these mines. In caving mines, the uniform extraction not means as equal extraction from blocks. In the uniform caving, controlling of caving propagation is one of the most critical factors in the stability of caving mines. Selection of advancement direction is one of the most important constraints in block caving and in the advancement direction controlling one of the critical aspects related to blocks precedency. So the goal of this research is to determine block precedence according to caving direction. It is crucial to control and validate the advancement direction to reach an optimum scheduling program. In this paper, an innovative approach is presented to control and predict the best advancement direction. MATLAB software is the framework of the presented model. The designer can find the desired direction by introducing a start and end points for caving propagation. Finally, its output can be used as input to scheduling programs of caving mines. Application and comparison of the model based on the advancement direction algorithms are validated using 98 using over 12 periods. The results show that the presented model respected to advancement direction and the model size is an accepted range for production planning problems.

Keywords


[1]     Moss, A., Diachenko, S., and Townsend, P.  (2006). “Interaction between the block cave and the pit slopes at Palabora mine, in Stability of rock slopes in open pit mining and civil engineering situations”. Johannesburg, The South African Institute of Mining and Metallurgy (SAIMM), 479-484.
[2]     Munro, D. D. (2013). “Incline caving as a massive mining method”. The Journal of The Southern African Institute of Mining and Metallurgy, 113: 555-563.
[3]     Laubscher, D. H. (1994). “Cave mining-the state of the art”. The Journal of The South African Institute of Mining and Metallurgy, 279-293.
[4]     Brown, E. T. (2002). “Block Cave Geomechanics”. JKMRC Monograph Series in Mining and Mineral Processing 3, The University of Queensland, ITASCA Consuling Group, INC, 108-123.
[5]     Thomas, G. P. (2012). “Cave Mining Techniques”. Mining Magazine, 2(1): 28-42.
[6]     Pourrahimian, Y., and Askari-Nasab, H. (2014). “An application of mathematical programming to determine the best height of draw in block-cave sequence optimisation”. Mining Technology (Transactions of the Institution of Mining and Metallurgy A), 123(3): 162-172.
[7]     Nezhadshahmohammad, F., Aghababaei, H., and Pourrahimian, Y. (2017). “Conditional draw control system in block-cave production scheduling using mathematical programming”. International Journal of Mining, Reclamation and Environment, 33(4): 1-24.
[8]     Nezhadshahmohammad, F., Pourrahimian, Y., and Aghababaei, H. (2018). “Presentation of a multi-index clustering technique for the mathematical programming of block-cave scheduling”. International Journal of Mining Science and Technology, 28(6): 941-950.
[9]     Verdugo, R., and Ubilla, J. (2004) “Geotechnical analysis of gravity flow during block caving”. Professor of Geotechnical Engineering, University of Chile, Chile, 195-200.
[10]  Alford, C., Brazil, M., and Lee, D. (2007). “Optimisation in Underground Mining”. In Handbook Of Operations Research In Natural Resources, Springer US, 561-577.
[11]  Chanda, E. K. C., and Dagdelen, K. (1995). “Optimal blending of mine production using goal programming and interactive graphics systems”. International Journal of Surface Mining, Reclamation and Environment, 9(4): 203-208.
[12]  Pourrahimian, Y., Askari-Nasab, H., and Tannant, D. (2013). “A multi-step approach for block-cave production scheduling optimization”. International Journal of Mining Science and Technology, 23(5): 739-750.
[13]  Diering, T. (2004). “Combining Long Term Scheduling and Daily Draw Control for Block Cave Mines”. In Massmin. Santiago, Chile, 486-490.
[14]  Chitombo, G. P. (2010). “Cave mining: 16 years after Laubscher’s 1994 paper ‘Cave mining - state of the art”. Mining Technology, 119(3): 132-141.
[15]  Butcher, R. J. (1999). “Design rules for avoiding draw horizon damage in deep level block caves”. The Journal of The South African Institute of Mining and Metallurgy, 151-156.
[16]  Yuan, S., and Grayson, R. L. (1994). “A large-scale work scheduling algorithm for underground coal mines”. SME Preprint, 1: 285-291.
[17]  Topal, E. (1998). “Long and short term production scheduling of the Kiruna iron ore mine, Kiruna, Sweden”. Master of Science Thesis, Colorado School of Mines, Golden, Colorado, 111-125.
[18]  Kuchta, M., Newman, A., and Topal, E. (2003). “Production Scheduling at LKAB’s Kiruna Mine Using Mixed-Integer Programming”. In SME Annual Meeting Preprint. Phoenix, Arizona, USA, pp. 55.
[19]  Martinez, M. A., and Newman, A. M. (2011). “A solution approach for optimizing long- and short-term production scheduling at LKAB’s Kiruna mine”. European Journal of Operational Research, 211(1): 184-197.
[20]  Khodayari, F., and Pourrahimian, Y. (2016). “Quadratic programming application in block-cave mining”. 1st International Conference on underground Mining, Santiago, Chile, 427-438.
[21]  Magda, R. (1994). “Mathematical model for estimating the economic effectiveness of production process incoal panels and an example of its practical application”. International, 34(1): 47–55.
[22]  Winkler, B. M. (1998). “A system for quality oriented mine production planning with MOLP”. In APCOM 98: Computer Applications in the Mineral Industries International Symposium, London, United Kingdom, 18-29.
[23]  Smith, M. L., Sheppard, I., and Karunatillake, G. (2003). “Using MIP for strategic life-of-mine planning of the lead/zinc stream at Mount Isa Mines”. In Proceedings of 24th international symposium, Application of computersin the mineral industry, Cape Town, South Africa, 465-474.
[24]  Sarin, S. C., and West-Hansen, J. (2005). “The long-term mine production scheduling problem”. IIE Transactions, 37(2): 109–121.
[25]  Epstein, R., Goic, M., Weintraub, A., Catalan, J., Santibanez, P., Urrutia, R., Cancino, R., Gaete, S., Aguayo, A., and Caro, F. (2012). “Optimizing Long-Term Production Plans inUnderground and Open-Pit Copper Mines”. Operations Research, 60(1): 4-17.
[26]  Nehring, M., Topal, E., and Little, J. (2010). “A new mathematical programming model for production schedule optimization in underground mining operations”. The Journal of The Southern African Institute of Mining and Metallurgy, 110: 437-446.
[27]  Rubio, E. (2014). “Block caving strategic mine planning using Risk-Return portfilio optimization”. In 3rd International Symposium on Block and Sublevel Caving (Caving 2014), R. Castro, Edito, Universidad de Chile: Santiago-Chile. 466-476.
[28]  Rubio, E., Caceres., C., and Scoble, M. (2004). “Towards an integrated approach to block cave planning”. In Massmin, Santiago, Chile, 128-134.
[29]  Becka, D., Arndtb, S., Thinc, I., Stonec, C., and Butcherd, R. (2006). “A conceptual sequence for a block cave in an extreme stress and deformation environment”. In Deep and High Stress Mining, Quebec City, Canada, 1-16.
[30]  Rahal, D., (2008). “Draw Control in Block Caving Using Mixed Integer Linear Programming”. In Sustainable Minerals Institute, The University of Queensland, pp. 342.
[31] Rahal, D., Dudley, J., and Hout, G.v. (2008). “Developing an optimised production forecast at Northparkes E48 mine using MILP”. In 5th International Conference and Exhibition on Mass Mining. Luleå Sweden, 51-58.
[32] Smoljanovic, M., Rubio, E., and Morales, N. (2011). “Panel Caving Scheduling Under Precedence Constraints Considering Mining System”. In 35th APCOM Symposium, Wollongong, NSW, Australia, 407-417.