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operational symptoms of components that may be obtained from vibration, pressure and
noise may be good indicators of an impending failure; and condition-monitoring system
may be conformed to such a condition. In another case, corrective repairing or replacement
of a component may give an opportunity for proactive control and maintenance of the other
components. As it is understood from the variety in maintenance work packages, different
equipment may require different maintenance policies, which serve in compliance with the
working environment of equipment, and need to be applicable in financial and practical
manner.
In this sense, the current study correlates the stochastic operating and maintenance behaviors of a system with an integrated maintenance model including corrective maintenance,
opportunistic maintenance and regular preventive inspections. The developed model allows
examining the effects of changeable parameters in a maintenance policy to the downtime
attitude of the system.
2 THE DEVELOPED MODEL
2.1 General methodology
The model evaluates mutual interactions between the downtime and uptime behaviors
of subsystems in operation, and manages lifetime and maintenance duration dataflow to
decide one or multiple of corrective, preventive, and opportunistic maintenance activities in the actualized timeframe. In the model, various modules run for the integration
of opportunistic maintenance to a policy that activates a proactive maintenance for
deteriorated subsystems in case of corrective maintenance of any other subsystem failing during working hours. A decision is given for the subsystem deterioration considering the expert opinions such that a defect giving any sign for a forthcoming failure is
considered as detectable during the inspections if this signing period overlaps with any
nearby inspection duration. For a better mimicking of system maintenance, administrative breaks were also considered in the model. The general simulation methodology can
be viewed in Figure 1.
Figure 1. Methodology of the simulation model.
operational symptoms of components that may be obtained from vibration, pressure and
noise may be good indicators of an impending failure; and condition-monitoring system
may be conformed to such a condition. In another case, corrective repairing or replacement
of a component may give an opportunity for proactive control and maintenance of the other
components. As it is understood from the variety in maintenance work packages, different
equipment may require different maintenance policies, which serve in compliance with the
working environment of equipment, and need to be applicable in financial and practical
manner.
In this sense, the current study correlates the stochastic operating and maintenance behaviors of a system with an integrated maintenance model including corrective maintenance,
opportunistic maintenance and regular preventive inspections. The developed model allows
examining the effects of changeable parameters in a maintenance policy to the downtime
attitude of the system.
2 THE DEVELOPED MODEL
2.1 General methodology
The model evaluates mutual interactions between the downtime and uptime behaviors
of subsystems in operation, and manages lifetime and maintenance duration dataflow to
decide one or multiple of corrective, preventive, and opportunistic maintenance activities in the actualized timeframe. In the model, various modules run for the integration
of opportunistic maintenance to a policy that activates a proactive maintenance for
deteriorated subsystems in case of corrective maintenance of any other subsystem failing during working hours. A decision is given for the subsystem deterioration considering the expert opinions such that a defect giving any sign for a forthcoming failure is
considered as detectable during the inspections if this signing period overlaps with any
nearby inspection duration. For a better mimicking of system maintenance, administrative breaks were also considered in the model. The general simulation methodology can
be viewed in Figure 1.
Figure 1. Methodology of the simulation model.