Increasingly complex and realistic models of manufacturing systems with failure-prone machines are formulated as stochastic optimal control problems. Partial characterization of their solutions are provided when possible along with their decomposition based on event frequencies. In the latter case, two-level decisions are constructed which are shown to be asymptotically optimal as the average time between successive short-term events becomes much smaller than that between successive long-term events. The striking novelty of this approach is that this is done without solving for the optimal solution, which is an insurmountable risk.
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