Fault maintenance trees: reliability centered maintenance via statistical model checking

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 11 Citations

Abstract

The current trend in infrastructural asset management is towards risk-based (a.k.a. reliability centered) maintenance, promising better performance at lower cost. By maintaining crucial components more intensively than less important ones, dependability increases while costs decrease. This requires good insight into the effect of maintenance on the dependability and associated costs. To gain these insights, we propose a novel framework that integrates fault tree analysis with maintenance. We support a wide range of maintenance procedures and dependability measures, including the system reliability, availability, mean time to failure, as well as the maintenance and failure costs over time, split into different cost components. Technically, our framework is realized via statistical model checking, a state-of-the-art tool for flexible modelling and simulation. Our compositional approach is flexible and extendible. We deploy our framework to two cases from industrial practice: insulated joints, and train compressors.
LanguageEnglish
Title of host publicationProceedings of the IEEE 62nd Annual Reliability and Maintainability Symposium, RAMS 2016
Place of PublicationUSA
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Print)978-1-5090-0248-1
DOIs
StatePublished - Jan 2016
EventIEEE 62nd Annual Reliability and Maintainability Symposium - Phoenix, United States
Duration: 25 Jan 201628 Jan 2016
Conference number: 62
http://www.asq0707.org/event/rams-2016-62nd-annual-reliability-maintainability-symposium/

Publication series

Name
PublisherIEEE

Conference

ConferenceIEEE 62nd Annual Reliability and Maintainability Symposium
Abbreviated titleRAMS 2016
CountryUnited States
CityPhoenix
Period25/01/1628/01/16
Internet address

Fingerprint

Model checking
Costs
Fault tree analysis
Asset management
Compressors
Statistical Models
Availability

Keywords

  • repairable systems
  • EWI-26747
  • METIS-315562
  • Maintenance
  • Fault Tree Analysis
  • IR-99367

Cite this

Ruijters, E. J. J., Guck, D., Drolenga, P., & Stoelinga, M. I. A. (2016). Fault maintenance trees: reliability centered maintenance via statistical model checking. In Proceedings of the IEEE 62nd Annual Reliability and Maintainability Symposium, RAMS 2016 USA: Institute of Electrical and Electronics Engineers. DOI: 10.1109/RAMS.2016.7447986
Ruijters, Enno Jozef Johannes ; Guck, Dennis ; Drolenga, Peter ; Stoelinga, Mariëlle Ida Antoinette. / Fault maintenance trees: reliability centered maintenance via statistical model checking. Proceedings of the IEEE 62nd Annual Reliability and Maintainability Symposium, RAMS 2016. USA : Institute of Electrical and Electronics Engineers, 2016.
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Ruijters, EJJ, Guck, D, Drolenga, P & Stoelinga, MIA 2016, Fault maintenance trees: reliability centered maintenance via statistical model checking. in Proceedings of the IEEE 62nd Annual Reliability and Maintainability Symposium, RAMS 2016. Institute of Electrical and Electronics Engineers, USA, IEEE 62nd Annual Reliability and Maintainability Symposium, Phoenix, United States, 25/01/16. DOI: 10.1109/RAMS.2016.7447986

Fault maintenance trees: reliability centered maintenance via statistical model checking. / Ruijters, Enno Jozef Johannes; Guck, Dennis; Drolenga, Peter; Stoelinga, Mariëlle Ida Antoinette.

Proceedings of the IEEE 62nd Annual Reliability and Maintainability Symposium, RAMS 2016. USA : Institute of Electrical and Electronics Engineers, 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Ruijters EJJ, Guck D, Drolenga P, Stoelinga MIA. Fault maintenance trees: reliability centered maintenance via statistical model checking. In Proceedings of the IEEE 62nd Annual Reliability and Maintainability Symposium, RAMS 2016. USA: Institute of Electrical and Electronics Engineers. 2016. Available from, DOI: 10.1109/RAMS.2016.7447986