equipment reliability and process variability. • Strategic Selection of Alternative 4: The analysis identifies Alternative 4 as the optimal investment path. By synchronizing the critical feeding, pumping, and screening circuits, this configuration enables a sustainable throughput of 4.96 Mtpa (2,718 t/h of wet feed), maintaining an OEE above 88% while controlling the transient choking effects observed under the expanded mass-pull condition. • Risk Mitigation and Resilience: A deterministic approach to capacity planning is no longer sufficient for complex orebodies. Stochastic modeling shows that, without the implementation of Alternative 4, the probability of meeting the 2030 production targets remains below 15%. This confirms that the proposed CAPEX is not merely an expansion initiative, but a necessary condition for operational resilience. • Economic Optimization (The Sweet Spot): The use of the Unitary VAC metric established a clear financial ceiling for the project. While Alternative 4 maintains a competitive cost structure (0.87–1.07 USD/t), any attempt to exceed 5.0 Mtpa drives the VAC to approximately 1.8 USD/t due to the need for major reinforcement or duplication of critical transport, pumping, and classification infrastructure, clearly identifying the point of diminishing returns for capital allocation. In conclusion, this research confirms that dynamic simulation is the most effective methodology for supporting brownfield investment decisions in complex concentrator systems. By revealing the migration of constraints and prioritizing capital toward the synchronization of feeding, pumping, and screening infrastructure, the Stochastic Dynamic Simulation framework enables Miski Mayo to move from reactive troubleshooting to proactive constraint management, strengthening long-term productive stability and economic viability under increasingly challenging mineralogical conditions. ACKNOWLEDGEMENTS The authors would like to express their sincere appreciation to Marilza Carneloz, Chief Executive Officer, and Akira Takahashi, Operations Director, for their leadership and support throughout this study. The authors also thank the Miski Mayo technical team and Hatch for their expertise in dynamic simulation, technical evaluation, and strategic analysis, which were fundamental to the successful completion of this work. REFERENCES Hulbert, D. G. (2003). Simulation, control and modelling of mineral processes. En Proceedings of the XX International Mineral Processing Congress. Randburg, Sudáfrica: Mintek. Lavoie, P., Navarra, P., & Kuhne, R. (2008). Dynamic simulation in iron ore pelletizing plants. Montreal, Canadá: Hatch/Rio Tinto Technical Publications.
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