Mobile decontamination of firefighters after hazardous missions is critical to limiting secondary contamination and health risks. Existing systems are typically constrained by fixed workflows, limited scalability, and minimal integration of real-time decision support. This study presents a risk-informed, adaptive operational framework implemented on the Arete Logic modular decontamination platform. The approach combines workflow mapping, discrete-event simulation, and safety–efficiency trade-off analysis to optimize throughput while maintaining contamination control. Baseline simulations revealed bottlenecks in rinse and drying zones. Optimization scenarios applying parallel stationing, dynamic routing, and time-based resource reallocation improved throughput and reduced cycle time without exceeding safety thresholds. Safety–efficiency analysis identified an operational “sweet spot” beyond which risk rises sharply. The study closes key gaps in existing research by integrating human factors, real-time control logic, and modular scalability into a unified framework, providing a basis for future field trials and multi-agency deployment.