Average cost per unit time control of stochastic manufacturing systems: Revisited

An optimal production planning for a stochastic manufacturing system is considered. The system consists of a single, failure-prone machine that produces a finite number of different products. The objective is to determine a rate of production that minimizes an average cost per unit time criterion where the demand is random. The results given in this paper are based on some large deviation estimates and the Hamilton–Jacobi–Bellman equations for convex functions.