An integrated modeling framework to determine robust operational regions in pharmaceutical water-for-injection distribution loops

Pharmaceutical manufacturing increasingly embraces digitalization to enhance reliability, ensure compliance and reduce downtime. This study introduces an integrated modeling framework designed to systematically determine robust operational regions (ROR) in water-for-injection (WFI) distribution loops, which are critical infrastructures subject to variable consumer demand and stringent regulatory constraints. Employing a structured workflow that combines first principles modeling, sensitivity-based parameter identifiability, and Monte Carlo simulations, the framework reliably captures the hydraulic behavior across operational conditions to guide process experts in establishing robust system operation. The approach addresses challenges arising from sparse data and limited sensor coverage, prevalent in current pharmaceutical operations. The application of the framework using industrial data demonstrated identification of conditions likely to trigger system alarms. Consequently, actionable setpoint recommendations were generated to ensure stable and alarm-free operation, offering a transferable blueprint for other fluid distribution networks. The results underscore the broader applicability of rigorous identifiability diagnostics as foundational tools to accelerate Pharma 4.0 adoption, sensor placement optimization, and proactive operational decision-making. • Developed an integrated framework combining mechanistic modeling, sensitivity analysis, and Monte Carlo simulations for robust WFI loop operation. • Successful application of the proposed framework, determining identifiable and relevant parameters to ensure model accuracy • Systematically identified robust operational regions (ROR) to proactively mitigate alarms. • Demonstrated practical applicability on industrial data from a large-scale WFI distribution loop.