Optimizing Mission Safety: Integrated Abort and Spare Support Policy

We investigate the risk management problem of a safety-critical system designed for time-critical missions. The system's operational component undergoes degradation modeled by a general continuous stochastic process, where component failure results in immediate system breakdown and significant safety risks. To improve system survivability, a finite number of identical spare components are provided for real-time replacement during the mission. Concurrently, a mission abort mechanism is triggered when safety hazards exceed acceptable thresholds. To balance mission success and system survival, we explore adaptive strategies for scheduling component replacements and mission abort decisions. The problem is formulated using a Markov decision process, and the monotonicity of the value function is demonstrated. Furthermore, we derive analytical insights into spare component availability and component degradation states to establish an optimal control-limit policy for replacements and mission aborts. Numerical experiments, conducted using a radar system as a case study, validate the proposed model's effectiveness in enhancing the operational reliability of safety-critical systems.