Imperfect predictive maintenance model for multi-state systems with multiple failure modes and element failure dependency
The objective of this study is to develop a practical statistical model for imperfect predictive maintenance based scheduling of multi-state systems (MSS) with...
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Main Authors: | , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2010
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/93527 http://hdl.handle.net/10220/6347 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | The objective of this study is to develop a practical
statistical model for imperfect predictive maintenance
based scheduling of multi-state systems (MSS) with
reliability dependent elements and multiple failure modes.
The system is modeled using a Markov state diagram and
reliability analysis is performed using the Universal
Generating Function (UGF) technique. The model is
simulated for a case study of a power generation transmission
system. The various factors influencing the
predictive maintenance (PdM) policy such as maintenance
quality and user threshold demand are examined and the
impact of the variation of these factors on system
performance is quantitatively studied. The model is found
to be useful in determining downtime schedules and
estimating times to replacement of an MSS under the PdM
policy. The maintenance schedules are devised based on a
"system-perspective" where failure times are estimated by
analyzing the overall performance distribution of the
system. Simulation results of the model reveal that a slight
improvement in the "maintenance quality" can postpone
the system replacement time by manifold. The consistency
in the quality of maintenance work with minimal variance
is also identified as a very important factor that enhances
the system's future operational and downtime event
predictability. Moreover, the studies reveal that in order to
reduce the frequency of maintenance actions, it is
necessary to lower the minimum user expectations from the
system, ensuring at the same time that the system still
performs its intended function effectively. The model
proposed can be utilized to implement a PdM program in
the industry with a few modifications to suit the individual
industry's needs. |
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