Controlling mission hazards through integrated abort and spare support optimization.

This study explores the risk management challenges associated with safety-critical systems required to execute specific missions. The working component experiences degradation governed by a continuous-time discrete-state Markov chain, whose failure leads to an immediate system breakdown and safety losses. To enhance system survivability, a limited number of identical spares are available for online replacement throughout the mission. At the same time, the mission abort action arises promptly upon encountering excessive safety hazards. To strike an optimal balance between mission completion and system survivability, we delve into the adaptive scheduling of component replacements and mission termination decisions. The joint decision problem of interest constitutes a finite-time Markov decision process with resource limitation, under which we analyze a series of structural properties related to spare availability and component conditions. In particular, we establish structured control-limit policies for both spare replacement and mission termination decisions. For comparison purposes, we evaluate the performance of various heuristic policies analytically. Numerical experiments conducted on the driver system of radar equipment validate the superior model performance in enhancing operational performance while simultaneously mitigating hazard risks.