Multiple Destination Influence on Production Scheduling in Multi-element Mines

Authors

Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran

Abstract

In multi-element deposits, different blocks are blended together to create a product with a predetermined quality. Generally, blending aims to obtain a special quality and quantity based on determining the processing plant or customer needs. However, blending causes different products based on the deposit properties. Thus, a block is blended with others to create one of many possible products. The present study aims to develop a mixed integer programming model for the production scheduling of iron ore mines. The model can consider different destinations for mine blocks. Each destination has its own specifications for the main element (Fe) and other existing elements such as sulfur and phosphorous. For this purpose, ten different scenarios were evaluated to investigate the effect of multiple products on production scheduling and Net Present Value (NPV) of the related project. Among the four selected scenarios, the mine was scheduled based on single product while multiple products were considered in scheduling in other scenarios. Based on the results, the maximum NPV in scenarios with multiple products is approximately 15% higher than that of the single product scenarios.

Keywords

References

1.     Peng, F., Walters, A., Geer, M. and Leonard, J., "Evaluation and prediction of optimum cleaning results", Coal Preparation, 4th edn., AIME, New York,  (1979), 101-110.
2.     Fytas, K. and Calder, P.N., "A computerized model of open pit short and long range production scheduling", in 19th APCOM Symposium. (1986), 109-119.
3.     White, J. and Olson, J., "Computer-based dispatching in mines with concurrent operating objectives", Min. Eng.(Littleton, Colo.);(United States),  Vol. 38, No. 11, (1986).
4.     Sundar, D.K. and Acharya, D., "Blast schedule planning and shiftwise production scheduling of an opencast iron ore mine", Computers &Industrial Engineering,  Vol. 28, No. 4, (1995), 927-935.
5.     Temeng, V.A., Otuonye, F.O. and Frendewey Jr, J.O., "Real-time truck dispatching using a transportation algorithm", International Journal of Surface Mining, Reclamation and Environment,  Vol. 11, No. 4, (1997), 203-207.
6.     Gholamnejad, J., Osanloo, M. and Khorram, E., "A chance constrained integer programming model for open pit long-term production planning", International Journal of Engineering Transactions A: Basics,  Vol. 4, No. 21, (2008), 407-418.
7.     Smith, M.L., "Integrating conditional simulation and stochastic programming: An application in production scheduling", Computer Application in the Materials Industries,. (2001), 203-208.
8.     Rehman, S.U. and Asad, M.W.A., "A mixed-integer linear programming (milp) model for short-range production scheduling of cement quarry operations", Asia-Pacific Journal of Operational Research,  Vol. 27, No. 03, (2010), 315-333.
9.     Zuckerberg, M., Van der Riet, J., Malajczuk, W. and Stone, P., "Optimal life-of-mine scheduling for a bauxite mine", Journal of Mining Science,  Vol. 47, No. 2, (2011), 158-165.
10.   Askari-Nasab, H., Eivazy, H., Tabesh, M. and Badiozamani, M., "A mathematical programming model for open pit short-term production scheduling", in SME Annual Meeting, Denver, Colorado, USA SME. (2011), 1-8.
11.   Rahmanpour, M. and Osanloo, M., "Pit limit determination considering blending requirements", in in Proceeding MPES., (2012), 564-575.
12.   Kumral, M. and Dowd, P., "Short-term mine production scheduling for industrial minerals using multi-objective simulated annealing", in APCOM 2002: 30 th International Symposium on the Application of Computers and Operations Research in the Mineral Industry., (2002), 731-741.
13.   Samanta, B., Bhattacherjee, A. and Ganguli, R., "A genetic algorithms approach for grade control planning in a bauxite deposit", in Proceedings of the 32nd International Symposium on Applications of Computers and Operations Research in the Mineral Industry, (2005), 337-342.
14.   Souza, M.J., Coelho, I.M., Ribas, S., Santos, H.G. and Merschmann, L.H.d.C., "A hybrid heuristic algorithm for the open-pit-mining operational planning problem", European Journal of Operational Research,  Vol. 207, No. 2, (2010), 1041-1051.
15.   Asad, M.W.A., "A heuristic approach to long-range production planning of cement quarry operations", Production Planning & Control,  Vol. 22, No. 4, (2011), 353-364.
16.   Sari, Y.A. and Kumral, M., "Mine production scheduling for poly-metallic mineral deposits: Extension to multiple processes", International Journal of Planning and Scheduling,  Vol. 2, No. 2, (2015), 134-153.
17.   Goodfellow, R.C. and Dimitrakopoulos, R., "Global optimization of open pit mining complexes with uncertainty", Applied Soft Computing,  Vol. 40, (2016), 292-304.
18.   Jélvez, E., Morales, N., Nancel-Penard, P., Peypouquet, J. and Reyes, P., "Aggregation heuristic for the open-pit block scheduling problem", European Journal of Operational Research,  Vol. 249, No. 3, (2016), 1169-1177.
19.   Mohammadi, S., Kakaie, R., Ataei, M. and Pourzamani, E., "Determination of the optimum cut-off grades and production scheduling in multi-product open pit mines using imperialist competitive algorithm (ICA)", Resources Policy,  Vol. 51, (2017), 39-48.
20.   Rahmanpour, M. and Osanloo, M., "Resilient decision making in open pit short-term production planning in presence of geologic uncertainty", International Journal of Engineering Transactions A: Basics,  Vol. 29, No. 7, (2016), 1022-1028.
21.   Kakha, G., G.  and Monjezi, M., "Push back design in two-element deposits incorporating grade uncertainty", International Journal of Engineering-Transactions B: Applications,  Vol. 30, No. 8, (2017), 1279-1287.
International Journal of Engineering
Volume 31, Issue 1
TRANSACTIONS A: Basics
January 2018
Pages 173-180

Files

Cited by

Share

How to cite

Statistics