This paper presents a modularized, easy-to-implement framework for predictive maintenance scheduling. With a modularization treatment of a maintenance scheduling model, a predictive maintenance scheduling model can be established by integrating components’ real-time, sensory-updated prognostics information with a classical preventive maintenance/condition-based maintenance scheduling model. With the framework, a predictive maintenance scheduling model for multi-component systems is established to illustrate the framework’s use; such a predictive maintenance scheduling model for multi-component systems has not been reported previously in the literature. A numerical example is provided to investigate the individual-orientation and dynamic updating characteristics of the optimal preventive maintenance schedules of the established predictive maintenance scheduling model and to evaluate the performance of these preventive maintenance schedules. It is hoped that the presented framework will facilitate the implementation of predictive maintenance policies in various industrial applications.
A Preventive Maintenance Scheduling Model of the Cluster Tool
