Optimal Dynamic Condition-Based Mode Switching Policy for Systems With Main and Auxiliary Components

In various complex systems, auxiliary components play a crucial role in mitigating potential negative effects on the main component. This paper examines systems comprising a main component and an auxiliary component that offers minimal repairs to the main component. While the main component operates online, the auxiliary component has the flexibility to switch between online and offline modes. The modes and failures of the auxiliary component have significant implications for the maintenance services adopted for both components, given their stochastic and economic dependence. During the online operation of the auxiliary component, it promptly performs minimal repairs, effectively minimizing the downtime costs of the main component. However, the auxiliary component itself may deteriorate over age, resulting in additional corrective maintenance expenses. Conversely, during the offline periods of the auxiliary component, prompt repairs to the main component are not feasible, leading to further downtime costs. Therefore, optimizing a dynamic condition-based mode switching policy of the auxiliary component becomes crucial in order to minimize the expected total costs effectively. To address this challenge, this paper formulates the optimization problem within a Markov decision process framework and explores the structural properties of the optimal policy, including monotonicity, control limit properties, and the impact of diverse cost scenarios on optimal decision-making. Furthermore, this paper validates the theoretical results by conducting a numerical example of a wind turbine system, which effectively confirms their practical applicability. Additionally, this paper compares the proposed policy with alternative heuristic policies and demonstrates a substantial decrease in expected total cost.