2069 without interfering; adding units beyond this limit generates waiting times that reduce individual utilization. Operational interferences — hang-ups, shift changes, secondary breaking, and maintenance — determine the fraction of the shift in which each piece of equipment is actively extracting, revealing that the actual capacity of the level is significantly lower than the nominal capacity. The dump infrastructure acts as a downstream constraint: if its capacity is insufficient, equipment waits to dump regardless of fleet size. The model explicitly integrates these three factors, determining the optimal number of LHDs as an emergent result of the actual system dynamics, not from a nominal productivity formula. 5.3 Haulage Fleet Sizing The sizing of the low-profile truck fleet faces an analogous tension. An insufficient truck fleet generates waiting times at dump stations that reduce LHD utilization, transferring the dominant constraint from the HL to the PL. An excessive fleet saturates the underground road network, increasing truck cycle times and reducing tonnage transported per fleet unit. Simulation enables identification of the equilibrium point between these two inefficiencies, delivering the system throughput curve as a function of number of trucks for each LHD fleet configuration. This joint analysis — LHD fleet versus truck fleet — enables optimization of the total system fleet composition, not just each subsystem independently, which can generate significant differences compared to the results of isolated analysis. As shown in Figure 3, the model builds the system throughput curve as a function of number of trucks, whose inflection point defines the optimal fleet size for the current configuration of the downstream subsystems. Figure 3 - System throughput as a function of haul truck fleet size (generic illustrative scenario). Output grows near-linearly while the haulage level is the binding constraint. Beyond the inflection point, road network congestion increases truck cycle times and each additional unit generates diminishing marginal returns. Identifying this threshold is a primary application of the calibrated simulation model in haulage fleet sizing decisions.
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