and dumps autonomously — is one of the highest-impact technological decisions in contemporary underground mining. Its evaluation requires comparing not only the individual productivity of equipment in manual versus autonomous mode, but the behavior of the complete system under each operating architecture. The model enables building and comparing scenarios with different automation configurations, varying the equipment-to-operator ratio and the performance parameters of autonomous mode — travel speed, positioning time at the loading point, frequency of required manual interventions. Output indicators include total system tonnage, effective equipment utilization, operator occupancy time, and identification of the bottleneck limiting the automation benefit in each configuration (Figure 4). This analysis addresses the fundamental question of the automation decision: not "is autonomous equipment faster than manual?" but "how much additional tonnage does the complete system generate under autonomous operation, considering all its interactions?". The answer to these two questions can be qualitatively different, and only integrated simulation can correctly answer the second. Figure 4 - System throughput and LHD utilization across manual and semi-automated operating scenarios (generic illustrative values). Throughput peaks at the 1 operator : 3 LHD ratio before declining due to operator overextension. LHD utilization decreases monotonically as each operator manages more units. The simulation identifies the ratio that maximises system-level throughput — the decision-relevant metric for technology transition investments. 5.5.Evaluation of MHS Expansion A third sizing scenario evaluates the expansion of the MHS upon incorporation of new production sectors. The model increases feed rates according to the proposed plan and
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