A Systems Engineering Approach to Modeling Reliability and Vulnerability in Automated Airport Baggage Networks

Automated baggage handling networks are critical to airport operations, yet their reliability and interdependencies make them vulnerable to disruptions ranging from electrical power outbreaks to mechanical failures or to cyber-attacks. This study proposes a systems engineering framework to model and quantify vulnerabilities in automated airport baggage handling systems (“BHS”), integrating classical models, failure mode analysis, and simulation techniques. By mapping BHS components (e.g., conveyor systems, electrical motors, sorting mechanism, IoT sensors and data) and their interactions, the framework identifies cascading failure risks and vulnerable points which threaten operational continuity. Using a combination of SysML (Systems Modelling Language) diagrams and agent-based simulations, the research evaluates scenarios such as ransomware attacks on control systems, sensor malfunctions, and peak-load congestion. Metrics like node criticality, recovery time, and redundancy efficiency are developed to prioritize mitigation strategies. The study analyses how adaptive redundancy, predictive maintenance solutions, and decentralized control architectures can reduce system-wide vulnerability exposure by up to 30 %. By bridging systems engineering principles with real-world baggage logistics, this approach provides actionable insights for designing reliable and resilient, self-healing networks. The findings advocate holistic vulnerability assessments in aviation infrastructure, ensuring compliance with evolving safety standards like ICAO's cybersecurity guidelines. This methodology is scalable to other automated transport systems, fostering safer, more reliable air travel ecosystems.