Cut-off Grade and Hauling Cost Varying with Benches in Open Pit Mining

Siwei He^1, , Xianli Xiang² and Gun Huang²

¹CAMCE Mining and Tunneling, Lougheed Hwy, Burnaby, Canada

²Guizhou University of Engineering Science, Bijie, Guizhou, China

Cite this paper:
Siwei He, Xianli Xiang and Gun Huang. Cut-off Grade and Hauling Cost Varying with Benches in Open Pit Mining. American Journal of Mining and Metallurgy. 2015; 3(2):54-57. doi: 10.12691/ajmm-3-2-3

Abstract

One of the most challenging problems geologist and engineer encountering in open pit mining is how much ore at benches can be extracted and sent to mill at the same time. Cutoff grade is playing an important role in solving this problem. The author, in this paper, presented a hauling cost-bench model, which directly impact cutoff grade. The cost model indicates that hauling cost, increasing with bench depth, largely depends upon the dynamic stripping ratio, representing the fundamental nature of resource and economic requirements of mineable ore at benches. The overall ore grade at benches is calculated according to operating cost model provided, while cutoff grade is found using trial-and-error technique based on resource model of a deposit. An example representing cut-off grade-bench curve is given, illustrating what relationship among cutoff grade, average grade and tonnage at benches and how much ore can be extracted and sent from these bench to mill. The example also shows how a way is found to mine out low-grade ore from one bench in a desired cut-off grade for an expected profit of the company. The cutoff grade vs. bench curve is a simple but useful tool for engineers to facilitate sound decision on how much ore tonnage at benches can be extracted and sent to mill at a time.

Keywords:
cutoff grade bench average grade expected profit ore tonnage stripping ratio

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References:

[1]	R.V. Ramani, K.V.K. Prasad, and R.L. Frantz, (March 1995),“Ore Reserve estimation: Myth and Reality of Computer Models”, Min. Res. Eng.4 (2), 15-28
[2]	Peter Darling, (2011), Mining Engineering Handbook, Third Edition,SME, USA, 401-403.
[3]	William A. Hustrulid, (2001), Underground Mining Methods: Engineering Fundamentals and International Case Studies,SME, 293-296.
[4]	William A. Hustrulid, ‎Mark Kuchta, ‎Randall K. Martin, (2013), Open Pit Mine Planning and Design,CRC Press, 334-496.
[5]	Xinming Tang, Yaolin Liu, Jixian Zhang, Wolfgang Kainz, (2007), Advances in Spatio-Temporal Analysis, CRC Press, 840-860.
[6]	G. Matheron, (1987), Springer Science & Business Media, Geostatistical Case Studies, 239-241.
[7]	A.E. Annels, (2012), Mineral Deposit Evaluation: A practical approach, Springer Science & Business Media, 321-323.
[8]	S.M. Rupprecht, (2012), “MINE DEVELOPMENT – ACCESS TO DEPOSIT”, the Southern African Institute of Mining and Metallurgy, 101-120.
[9]	Bruce A. Kennedy,(1990), Surface Mining, Second Edition, SME, 466-467.