AI 中文总结
该研究提出一种混合规划方法，用于推导串联系统的基于 prognostics 的预测性维护策略，该策略参数少、效率高且抗过拟合能力强，在预防性更换和订购场景中性能可媲美优化基准策略。
AI 中文摘要
我们提出一种混合规划方法，用于推导基于 prognostics 的预测性维护策略。该方法考虑了可用的决策选项、prognostic 模型提供的系统未来状态信息，以及基础更新-奖励过程的成本。它生成的策略仅由少数参数定义，这些参数可基于理论考量或通过从逐次故障数据中优化确定。我们在两种独立的预测性维护决策场景（预防性更换和预防性订购）中展示了该方法的潜力。数值研究表明，推导得到的策略性能可与优化基准策略相媲美，同时效率显著更高且对过拟合的鲁棒性更强。
英文摘要
We propose a hybrid planning method for deriving prognostics-based predictive maintenance policies. The method accounts for the available decision options, the information on the future state of the system provided by a prognostic model, and the costs of the underlying renewal-reward process. It results in policies defined by only a few parameters, which can be determined based on theoretical considerations or by optimization from run-to-failure data. We demonstrate the potential of the method in two separate predictive maintenance decision settings: preventive replacement and preventive ordering. Numerical investigations show that the derived policies rival the performance of optimized benchmark policies, while being significantly more efficient and robust against overfitting.
