Large-scale mine production scheduling optimisation with mill blending constraints at Newmont's Twin Creeks Operation

Abstract

This paper discusses the strategic mine planning process at Newmont's Twin Creeks Operation. A multi-period Mixed Integer Liner Programming (MILP) model is utilised to optimise a large scale, complex operation with multiple open pits and underground mine sources under tight process blending constraints with the option to stockpile. In addition to life-of-mine production scheduling optimisation using MILP, the strategic planning process includes cost analysis, phase design validations and sensitivity to constraints such as mining rates, mill blending or throughput. Through this planning approach, Twin Creeks Operation is realising significant value from cost reductions and higher near term free cash flow resulting in increases to life-of-mine net present value.

Keywords

Open Pit Mining Production Scheduling Optimisation

Get full access to this article

View all access options for this article.

References

Asad

M. W. A.

and Dimitrakopoulos

2012. Performance evaluation of a new stochastic network flow approach to optimal open pit mine design-application at a gold mine, Journal of the Southern African Institute of Mining and Metallurgy, 112, (7), 649–655.

Askari-Nasab

, Awuah-Offei

and Eivazy

2010. Large-scale open pit production scheduling using mixed integer linear programming, International Journal of Mining and Mineral Engineering, 2, (3), 185–214.10.1504/IJMME.2010.037624

Clark

and Dagdelen

2007. Finding added value at Newmont, Mining Magazine, 196, (4), 29–35.

Dagdelen

1996. Formulation of open pit scheduling problem including sequencing as MILP, Internal Report. Golden, CO, Mining Engineering Department, Colorado School of Mines.

Dagdelen

and Kawahata

2007. Opportunities in multi-mine planning through large scale mixed integer linear programming optimization , 33rd International Symposium on Application of Computers and Operations Research in the Mineral Industry (APCOM), Santiago, Chile, 337–342.

Dagdelen

and Kawahata

2008. Value creation through strategic mine planning and cutoff grade optimization, Mining Engineering. Society for Mining, Metallurgy and Exploration (SME), 60, (1), 39–45.

Goodfellow

and Dimitrakopoulos

2013. Algorithmic integration of geological uncertainty in pushback designs for complex multiprocess open pit mines, Mining Technology, 122, (2), 67–77.10.1179/147490013X13639459465736

Goodfellow

and Dimitrakopoulos

2015. Global optimization of open pit mining complexes with uncertainty, Applied Soft Computing, 40, 292–304. doi:10.1016/j.asoc.2015.11.038.

Hoerger

, Bachmann

, Criss

and Shortridge

1999. Long term mine and process scheduling at Newmont's Nevada operations , 28th International Symposium on Application of Computers and Operations Research in the Mineral Industry (APCOM), 739–747.

10.

Huang

, Cai

and Banfield

A. F.

2009. A new short- and medium-term production planning tool – Minesight® Schedule Optimizer (MSSO), SME Preprint 09-079, Denver, Colorado.

11.

IBM. 2014. IBM ILOG CPLEX Optimizer . www.ibm.com.

12.

Kawahata

, Schumacher

and Hufford

2013. Mine production scheduling optimization at Newmont's Twin Creeks Mine, Mining Engineering. Society for Mining, Metallurgy and Exploration (SME), 65, (6), 49–54.

13.

Kuchta

, Newman

and Topal

2004. Implementing a production schedule at LKAB's Kiruna Mine. Interfaces, 34, (2), 124–134.10.1287/inte.1030.0059

14.

Maptek. 2009. Chronos scheduler, Sydney, Maptek Software.

15.

Minemax. 2012. Minemax scheduler strategic mine schedule optimisation white paper , Perth, Minemax.

16.

Montiel

and Dimitrakopoulos

2015. Optimizing mining complexes with multiple processing and transportation alternatives: An uncertainty-based approach, European Journal of Operational Research, 247, (1), 166–178. doi:10.1016/j.ejor.2015.05.002.

17.

Montiel

, Dimitrakopoulos

and Kawahata

2015. Globally optimising open-pit and underground mining operations under geological uncertainty, Mining Technology (TIMM A), 125, (1), 2–14. doi:10.1179/1743286315Y.27.

18.

Newmont. 2014. 2013 Newmont Annual Report and Form 10-K , Greenwood Village, Colorado, Newmont Mining Corporation.

19.

Ramazan

and Dimitrakopoulos

2004. Traditional and new MIP models for production scheduling with in-situ grade variability, International Journal of Surface Mining, Reclamation and Environment, 18, (2), 85–98.10.1080/13895260412331295367

20.

Seymour

1996. Pit-limit parameterization from modified three-dimensional Lerches-Grossmann algorithm, SME Transactions, 298, 1860–1864.

21.

Stone

, Froyland

, Menabde

, Law

, Rasyar

and Monkhouse

2004. “Blasor – Blended iron-ore mine planning optimisation at Yandi”. Orebody Modelling and Strategic Mine Planning . In: Proceedings of the International Symposium, 285–288, Preprint, Carlton, Victoria: AIMM.

22.

Urbaez

and Dagdelen

1999. Implementation of linear programming model for optimum open pit production scheduling problem, SME Annual Meeting Preprint, Denver, Colorado, 99–108.

23.

Whittle

2009. The global optimizer works – what next? . Advances in Orebody Modelling and Strategic Mine Planning I. The Australasian Institute of Mining and Metallurgy, Melbourne, 3–5.