Existing research on maintenance policy optimization often assumes that the failure intensity functions of the system under maintenance are primarily altered by the effectiveness of maintenance. However, in practical scenarios, these functions can also undergo modifications due to innovation-related replacements. This paper focuses on systems with finite operating lifetimes and under the situation that the precise timing of innovation-related modifications is uncertain. The system undergoes preventive maintenance once it reaches a certain age, and failures occurring between these preventive maintenance actions are addressed through minimal repairs. This paper introduces a comprehensive framework for optimizing both prior and after innovation replacement preventive maintenance policies, with the objective of minimizing the total expected cost. The paper also presents optimal resource allocation strategies for innovation replacement development. Furthermore, we extend the framework to model imperfect preventive maintenance, in which each maintenance action only partially restores the system. Analytical maintenance policy is addressed and numerical examples are provided to illustrate the practical applications of the proposed methodologies. The proposed framework lowers lifecycle maintenance cost and outage time while maintaining reliability. For asset managers, it provides an interpretable, ready-to-implement rule that translates monitoring and cost inputs into executable maintenance schedules and defensible budget plans.
Wu et al. (Wed,) studied this question.