摘要

When we schedule a system to perform a task, a factor that should be taken into account is the remaining useful life prognostics of the system. This prognostics of the system may depend not only on the health state of the system, but also on the characteristics of the task to be performed. Assuming such prognostics is available at the time of system scheduling, the problem is to find a method to schedule the system, which can improve the expected profit rate. Two system life models were proposed for the case considered in this paper. Due to the dynamic nature of the problem, a global optimal policy is hard to find, we proposed an approach based on the approximated expected profit rate to schedule the systems. The approach is validated through simulations compared with a number of other task scheduling rules to show the advantage of the proposed approach. We also find the optimal global stationary result by exhaustive search of small scheduling problems of few systems and tasks to compare with the proposed approximate one. Further numerical analyses are presented to demonstrate the process of determining a decision variable and the sensitivity analysis in terms of a cost parameter.