Advantages of reliability-adaptive system operation for maintenance planning (bibtex)
by , ,
Abstract:
Intelligent mechatronic systems other the possibility to adapt system behavior to current dependability. This can be used to assure reliability by controlling system behavior to reach a pre-defined lifetime. By using such closed loop control, the margin of error of useful lifetime of an individual system is lowered. It is also possible to change the pre-defined lifetime during operation, by adapting system behavior to derate component usage. When planning maintenance actions, the remaining useful lifetime of each individual system has to be taken into account. Usually, stochastic properties of a fleet of systems are analyzed to create maintenance plans. Among these, the main factor is the probability of an individual system to last until maintenance. If condition-based maintenance is used, this is updated for each individual system using available information about its current state. By lowering the margin of error of useful lifetime, which directly corresponds to the time until maintenance, extended maintenance periods are made possible. Also using reliability-adaptive operation, a reversal of degradation driven maintenance planning is possible where a maintenance plan is setup not only according to system properties, but mainly to requirements imposed by maintenance personnel or infrastructure. Each system then adapts its behavior accordingly and fails according to the maintenance plan, making better use of maintenance personnel and system capabilities at the same time. In this contribution, the potential of maintenance plan driven system behavior adaptation is shown. A model including adaptation process and maintenance actions is simulated over full system lifetime to assess the advantages gained.
Reference:
Meyer, T.; Kaul, T.; Sextro, W.: Advantages of reliability-adaptive system operation for maintenance planning. Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, 2015. (Preprint: http://www.tobi-meyer.de/Meyer2015a.pdf)
Bibtex Entry:
@INPROCEEDINGS{Meyer2015a,
  howpublished = {Conference Proceedings},
  author = {Tobias Meyer AND Thorben Kaul AND Walter Sextro},
  title = {Advantages of reliability-adaptive system operation for maintenance
	planning},
  booktitle = {Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision
	and Safety for Technical Processes},
  year = {2015},
  pages = {940-945},
  abstract = {Intelligent mechatronic systems other the possibility to adapt system
	behavior to current dependability. This can be used to assure reliability
	by controlling system behavior to reach a pre-defined lifetime. By
	using such closed loop control, the margin of error of useful lifetime
	of an individual system is lowered. It is also possible to change
	the pre-defined lifetime during operation, by adapting system behavior
	to derate component usage. When planning maintenance actions, the
	remaining useful lifetime of each individual system has to be taken
	into account. Usually, stochastic properties of a fleet of systems
	are analyzed to create maintenance plans. Among these, the main factor
	is the probability of an individual system to last until maintenance.
	If condition-based maintenance is used, this is updated for each
	individual system using available information about its current state.
	By lowering the margin of error of useful lifetime, which directly
	corresponds to the time until maintenance, extended maintenance periods
	are made possible. Also using reliability-adaptive operation, a reversal
	of degradation driven maintenance planning is possible where a maintenance
	plan is setup not only according to system properties, but mainly
	to requirements imposed by maintenance personnel or infrastructure.
	Each system then adapts its behavior accordingly and fails according
	to the maintenance plan, making better use of maintenance personnel
	and system capabilities at the same time. In this contribution, the
	potential of maintenance plan driven system behavior adaptation is
	shown. A model including adaptation process and maintenance actions
	is simulated over full system lifetime to assess the advantages gained.},
  comment = {Preprint: \url{http://www.tobi-meyer.de/Meyer2015a.pdf}},
  doi = {10.1016/j.ifacol.2015.09.647},
  keywords = {Adaptive systems, Reliability analysis, Availability, Adaptive control,
	Maintenance, Self-optimizing systems, Self-optimizing control, Stochastic
	Petri-nets}
}
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