Graph Optimization for Failure Propagation in Intermittent Systems-of-Systems: Railway Use Case

Effective failure management is crucial in complex systems, where multiple interconnected components can trigger cascading failures, leading to operational disruptions and safety risks. This paper introduces a temporal graph-based approach to model structural and dynamic dependencies between system components, capturing both persistent connections as well as time-dependent interactions that influence failure propagation. We leverage this model to explore how graph-theoretic problems can be applied to identify the most critical components within such complex systems. By formulating and solving graph optimization problems, we gain insights into failure anticipation, risk mitigation, and targeted intervention strategies to enhance the system resilience and optimize predictive maintenance. To demonstrate the applicability of our approach, we applied the proposed model to a railway transportation system, focusing on the ERTMS/ETCS standard. We illustrate how key components are interconnected and analyze how failures originating in one component can propagate throughout the system.