Maintenance Scheduling Using Monitored Parameter Values

Applications of the reliability methods in maintenance scheduling have been widely investigated in the literature considering failure times. However, information obtained using condition monitoring devices, whenever possible is being used more and more in industries for maintenance scheduling. This trend is accelerated by the availability of reliable sensors and a rapid development in information technologies. The monitored parameter values (MPV) may explain the failure characteristics and influence the maintenance scheduling of a system. There are several reliability models that can be used to model MPV for maintenance scheduling. These models include regression models, proportional hazards family and accelerated failure time family. The latter two appear to be suitable for practical applications.The paper describes the models that can be used to model the MPV. Some guidelines for selection of suitable models for a given dataset are also discussed. These models are used to estimate the relative importance of the MPV in explaining the failure characteristics. Once the relative importance of the MPV is estimated, either graphical, numerical, or analytical methods can be used for maintenance scheduling based on the MPV. Maintenance cost models that include planned and unplanned maintenance costs are further extended to include the MPV. Graphical methods such as the total time on tests-plot or the cumulative intensity plot can be used to determine the optimum maintenance interval.The applications of reliability models and graphical methods for determination of the optimum maintenance time interval are illustrated with field failure data. The proposed approach can be used for repairable as well as non-repairable systems.