Managing productivity and improving efficiency for a healthy return on capital employed have become key mining industry strategies under prevailing tough global market conditions. However, achieving this in a multisystem environment such as a mining operation can be daunting. The field of discrete event simulation offers some relief, giving engineering teams insight into multivariable systems and stochastic processes. It allows for integrated system thinking and domain expertise to be woven into project thinking fibre. Directed system optimisation and therefore improved efficiency becomes possible. Furthermore, capital discipline accrues from optimal upgrade investments. This paper illustrates the practical application of this approach by reviewing a typical case study for a direct shipping iron ore operation. Dynamic simulation was used to establish maximum processing plant capacity under varying material characteristics and identify capital-efficient upgrades for increasing production.The study started with descriptive statistical analysis of existing data. Discrete equipment and system capacities were defined, followed by static plant mass balance calculations to establish bottlenecks and overall static capacity. Equipment uptime' and downtime' analyses established system and overall plant availability and utilisation. From this information, a dynamic simulation model could then be developed and initially calibrated against actual plant performance to verify its robustness. Once confirmed to accurately represent existing plant dynamics, system capacity response to variable changes could be tested to ultimately determine maximum plant capacity. Additionally, plant optimisation was incorporated to arrive at optimal upgrade points. Maximum capacity and necessary upgrades were established as a function primarily of feed size distribution. Additionally, the interfacing effects of rehandling feed material to the final product grade and potentially to life-of-mine were established as important outcomes. The results of the study illustrate the value of using dynamic simulation models to realistically and cost-effectively increase throughput.CITATION:Cele, W, Furstenberg, L, Richter, M and Steenkamp, N, 2015. Capacity evaluation of iron ore processing facilities utilising dynamic simulations, in Proceedings Iron Ore 2015, pp 597-604 (The Australasian Institute of Mining and Metallurgy: Melbourne).