Authors: Khodayari, F; Pourrahimian, Y; Ben-Awuah, E

Open access courtesy of:

Cite As:
Khodayari, F, Pourrahimian, Y & Ben-Awuah, E 2018, 'Application of mathematical modelling for draw control under material flow uncertainty', in Y Potvin & J Jakubec (eds), Proceedings of the Fourth International Symposium on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 815-822.

Download citation as:   ris   bibtex   endnote   text   Zotero


Abstract:
Production scheduling is one of the key steps in the decision-making process of any ‎mining operation. In block caving, it is the choice of the amount of caved rock to ‎extract from drawpoints in different periods. One of the main differences between ‎block caving and other mining methods is the influence of the material flow on ‎production, and draw control in general. Achieving an optimum production schedule ‎without consideration of the cave rate and material flow could be unrealistic and impractical as the ‎movements of material between drawpoints will result in unexpected production ‎grades and tonnages. In this paper, a stochastic mixed integer optimisation model is ‎proposed to optimise the production schedule during the life of the mine. The ‎uncertainties of production grades and tonnages are captured by defining a number of ‎scenarios that represent the probable movements of fragmented rock between ‎drawpoints in the same neighbourhood. The decision variables in the formulation are based on the slice model, which means that the mathematical ‎solution determines which slices are extracted from drawpoints in each period of production. The goal ‎is to maximise the net present value of the project during the life of the mine and ‎minimise the deviations of production grades and tonnages from the defined goals in ‎all probable scenarios resulting from the movements of the fragmented rock between ‎drawpoints. Application of the proposed model in caving operations can not only ‎improve the profitability of the project, but also increase the confidence of the ‎production schedule. MATLAB was used for programming and CPLEX for solving the ‎model. The designed graphical user interface, with the capability of adding different ‎technical and operational constraints, will be a flexible tool for mine planners to ‎control the draw based on the company’s goals during the life of the mine.‎ Keywords: block caving, production scheduling, draw control, material flow, stochastic ‎optimisation

Keywords:

References:
Diering, T 2004, ‘Computational considerations for production scheduling of block cave mines’, in A Karzulovic & MA Alfaro (eds), Proceedings of MassMin 2004, Instituto de Ingenieros de Chile, Santiago, pp. 135–140.
Khodayari, F & Pourrahimian, Y 2014, ‘Determination of the best height of draw in block cave sequence optimization’, in R Castro (ed.), Proceedings of the 3rd International Symposium on Block and Sublevel Caving, Universidad de Chile, Santiago,
pp. 457–465.
Khodayari, F & Pourrahimian, Y 2015a, ‘Determination of development precedence for drawpoints in block-cave mining’, in MP Nicolai (ed.), Proceedings of the 5th International Symposium: Mineral Resources and Mine Development, RWTH Aachen University, Aachen, pp. 383–391.
Khodayari, F & Pourrahimian, Y 2015b, ‘Mathematical programming applications in block-caving scheduling: a review of models and algorithms’, International Journal of Mining and Mineral Engineering, vol. 6, no. 3, pp. 234–257.
Khodayari, F & Pourrahimian, Y 2017, ‘Production scheduling in block caving with consideration of material flow’, Aspects in Mining and Mineral Science, vol. 1, no. 1.
Laubscher, DA 2000, A Practical Manual on Block Caving, prepared for International Caving Study, Julius Kruttschnitt Mineral Research Centre, Indooroopilly, and Itasca Consulting Group, Inc., Brisbane.
Pourrahimian, Y, Askari-Nasab, H & Tannant, D 2013, ‘A multi-step approach for block-cave production scheduling optimization’, International Journal of Mining Science and Technology, vol. 23, no. 5, pp. 739–750.
Rahal, D, Dudley, J & Hout, Gv 2008, ‘Developing an optimised production forecast at Northparkes E48 mine using MILP’,
in H Schunnesson & E Nordlund (eds), Proceeding of MassMin 2008, Luleå University of Technology, Luleå, pp. 227–236.
Rubio, E 2002, Long Term Planning of Block Caving Operations Using Mathematical Programming Tools, MSc thesis, The University of British Columbia, 126 p.




© Copyright 2018, Australian Centre for Geomechanics (ACG), The University of Western Australia. All rights reserved.
Please direct any queries to or error reports to repository-acg@uwa.edu.au