Authors: Isabel, A; Olonbayar, U; de Hennin, S; McKenna, L; Cuthbert, B

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DOI https://doi.org/10.36487/ACG_repo/2645_27

Cite As:
Isabel, A, Olonbayar, U, de Hennin, S, McKenna, L & Cuthbert, B 2026, 'Oyu Tolgoi underground: mine production modelling of a coupled material handling system ', in A van As, D Cumming-Potvin & J Wesseloo (eds), Caving 2026: Proceedings of the Sixth International Conference on Block and Sublevel Caving, Australian Centre for Geomechanics, Perth, pp. 1-11, https://doi.org/10.36487/ACG_repo/2645_27

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Abstract:
The Oyu Tolgoi underground mine has a coupled material handling system that is comprised of multiple fixed plant machinery and heavy mobile equipment that aims to minimise delays using an integrated asset management calendar. Realising throughput across the coupled value chain to ensure that forecasting accurately reflects operations offers its challenges to the mine planning process. Throughput forecasting focuses on 2 primary crushers located approximately 1,300 m below the Gobi Desert, which feed either a conveyor system or a shaft hoist to surface. Ore is sourced from multiple production panels, with Panel 0 currently in steady-state production and Panel 2 North in ramp-up, while additional panels are under development. Each panel comprises hundreds of drawpoints that are mucked by loaders into orepasses. Material flows through truck chutes where road trains are loaded. The trucks then haul the ore to one of the 2 primary crushers. The material handling system is tightly coupled, comprising a combination of parallel and series components whose individual capacities collectively govern overall system performance. Each link in the chain is subject to specific capacity constraints that directly influence system throughput. The cave systems themselves impose additional operating rules and objectives, including panel-specific draw control and cave draw strategies. As production ramps up through the ongoing construction and commissioning of additional drawpoints, the actual throughput performance of each system component is statistically evaluated to inform planning and forecasting input parameters. This paper outlines the structured process used to identify and map system connections and constraints, integrate maintenance calendars, apply time usage models for each sub system, and develop schedules that are compliant with the governing cave rules and draw strategies for each panel.

Keywords: material handling system, constraints, time usage model, cave production planning, asset management calendar

References:
de Hennin, S 2023, Mining Systems Variability and Buffers, Rio Tinto internal publication, Brisbane.
de Hennin, S 2024, Dynamic System Constraint Analysis Methods, Rio Tinto internal publication, Brisbane.
de Hennin, S 2025, Systems Thinking: A Framework for Modelling the Capacity of a Mining System Considering Reliability, Availability, Planned Downtime, and Buffering, Rio Tinto internal publication, Brisbane.
Institute of Electrical and Electronics Engineer 2007, 493-2007 - IEEE Recommended Practice for the Design of Reliable Industrial and Commercial Power Systems, Institute of Electrical and Electronics Engineer, New York,
Modarres, M 2016, Reliability Engineering and Risk Analysis, CRC Press, Singapore.




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