This paper proposes a generalized hybrid maintenance policy for maintenance scheduling with the help of both time-based maintenance and condition-based maintenance techniques, in which three-type product lifetime probabilistic models are utilized. A dispersion of lifetime estimates-based switcher is proposed to recommend the choice of time-based maintenance or condition-based predictive maintenance schedules in a real-time manner. Within the condition-based predictive maintenance policy, which is a part of the hybrid maintenance policy, a novel weighted average of the maintenance schedules is proposed to recommend maintenance acts, which are estimated based on two types of product lifetime probabilistic models namely type-II and type-III lifetime probabilistic models. The hybrid maintenance policy includes the classical time-based maintenance policy, the traditional condition-based predictive maintenance policy, and the proposed condition-based predictive maintenance policy as special cases. An extensive numerical investigation for the stochastic linear degradation model verifies the effectiveness of the proposed hybrid maintenance policy, highlighting the existence of a special space among time-based maintenance and condition-based predictive maintenance polices, which provides even better maintenance performance than a solely condition-based predictive maintenance policy.

中文翻译：

---

一种通用的基于三类寿命概率模型的混合维护策略，带有用于基于时间的预防性维护和基于条件的维护的实用切换器

本文在基于时间的维护和基于状态的维护技术的帮助下，提出了一种用于维护调度的广义混合维护策略，其中利用了三类产品寿命概率模型。提出了基于寿命估计的分散切换器，以实时推荐基于时间的维护或基于条件的预测性维护计划的选择。在作为混合维护策略一部分的基于状态的预测性维护策略中，提出了一种新颖的维护计划加权平均值来推荐维护行为，这些行为是基于两种类型的产品寿命概率模型进行估计的，即类型 II和 III 型寿命概率模型。混合维护策略包括经典的基于时间的维护策略、传统的基于状态的预测性维护策略以及作为特例提出的基于状态的预测性维护策略。随机线性退化模型的广泛数值研究验证了所提出的混合维护策略的有效性，突出了基于时间的维护和基于条件的预测性维护策略之间的特殊空间的存在，这提供了比单独条件更好的维护性能基于预测性维护策略。