Pre-Failure Service-Capacity Propagation and Dynamic Mission Reliability in Complex Industrial Systems
Abdulla Saeed Alhebsi
Abstract
Complex technological systems can lose mission capability before widespread physical component failure occurs. This study develops a dynamic reliability framework coupling a literature-anchored physical cascading mechanism with finite-capacity technical, information, human-decision, and response (T–I–HD–R) services. Directed work transfer, service capacity, backlog, and propagation delay are modeled explicitly so that operational congestion can propagate across heterogeneous functions. A synthetic safety-critical continuous-process system compares physical-only, heterogeneous-operational, and combined representations. In 10,000-replication principal experiments, combined mission reliability was 0.2080 (95% CI 0.2002–0.2161); 22.60% of runs satisfied the physical criterion but failed operationally. Global uncertainty screening across 21,600 additional runs retained this modeled pathway throughout the sampled space. Controlled capacity experiments showed that isolated human-decision expansion did not improve reliability when response capacity remained constrained, whereas coordinated expansion substantially improved reliability. Pure transfer delay sometimes buffered downstream demand, demonstrating mechanism-dependent delay effects. The framework extends dynamic reliability analysis by representing pre-failure work-transfer congestion as a reliability-relevant pathway that complements physical cascading failure.