IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v149y2016icp1-13.html
   My bibliography  Save this article

Stochastic hybrid automaton model of a multi-state system with aging: Reliability assessment and design consequences

Author

Listed:
  • Chiacchio, F.
  • D’Urso, D.
  • Manno, G.
  • Compagno, L.

Abstract

Dynamic reliability aims to relax the rigid hypotheses of traditional reliability enabling the possibility to model multi-state systems and consider changes of the nominal design condition of a system. The solution of such type of models is a complex task that cannot be tackled with analytical techniques and must involve other types of formalisms based on simulation. One of the most promising simulation approach is Stochastic Hybrid Automaton (SHA), able to breakdown a system into a physical and a stochastic model that are coupled together with shared variables and synchronising mechanisms.

Suggested Citation

  • Chiacchio, F. & D’Urso, D. & Manno, G. & Compagno, L., 2016. "Stochastic hybrid automaton model of a multi-state system with aging: Reliability assessment and design consequences," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 1-13.
    • Handle: RePEc:eee:reensy:v:149:y:2016:i:c:p:1-13
    DOI: 10.1016/j.ress.2015.12.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015003592
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2015.12.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Merle, G. & Roussel, J.-M. & Lesage, J.-J., 2011. "Algebraic determination of the structure function of Dynamic Fault Trees," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 267-277.
    2. Alan Hawkes & Lirong Cui & Zhihua Zheng, 2011. "Modeling the evolution of system reliability performance under alternative environments," IISE Transactions, Taylor & Francis Journals, vol. 43(11), pages 761-772.
    3. Manno, G. & Chiacchio, F. & Compagno, L. & D'Urso, D. & Trapani, N., 2014. "Conception of Repairable Dynamic Fault Trees and resolution by the use of RAATSS, a Matlab® toolbox based on the ATS formalism," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 250-262.
    4. Marseguerra, M. & Zio, E. & Devooght, J. & Labeau, P.E., 1998. "A concept paper on dynamic reliability via Monte Carlo simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 47(2), pages 371-382.
    5. Chiacchio, F. & Cacioppo, M. & D'Urso, D. & Manno, G. & Trapani, N. & Compagno, L., 2013. "A Weibull-based compositional approach for hierarchical dynamic fault trees," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 45-52.
    6. Ghosh, Rahul & Kim, DongSeong & Trivedi, Kishor S., 2013. "System resiliency quantification using non-state-space and state-space analytic models," Reliability Engineering and System Safety, Elsevier, vol. 116(C), pages 109-125.
    7. Enrico Zio, 2013. "Monte Carlo Simulation: The Method," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 19-58, Springer.
    8. Enrico Zio, 2013. "The Monte Carlo Simulation Method for System Reliability and Risk Analysis," Springer Series in Reliability Engineering, Springer, edition 127, number 978-1-4471-4588-2, February.
    9. Enrico Zio, 2013. "System Reliability and Risk Analysis by Monte Carlo Simulation," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 59-81, Springer.
    10. Enrico Zio, 2013. "System Reliability and Risk Analysis," Springer Series in Reliability Engineering, in: The Monte Carlo Simulation Method for System Reliability and Risk Analysis, edition 127, chapter 0, pages 7-17, Springer.
    11. Daniele Codetta-Raiteri & Luigi Portinale, 2014. "Approaching dynamic reliability with predictive and diagnostic purposes by exploiting dynamic Bayesian networks," Journal of Risk and Reliability, , vol. 228(5), pages 488-503, October.
    12. H Zhang & F Dufour & Y Dutuit & K Gonzalez, 2008. "Piecewise deterministic Markov processes and dynamic reliability," Journal of Risk and Reliability, , vol. 222(4), pages 545-551, December.
    13. Chiacchio, F. & Compagno, L. & D'Urso, D. & Manno, G. & Trapani, N., 2011. "Dynamic fault trees resolution: A conscious trade-off between analytical and simulative approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1515-1526.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cheng, Ruijun & Cheng, Yu & Chen, Dewang & Song, Haifeng, 2021. "Online quantitative safety monitoring approach for unattended train operation system considering stochastic factors," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Dong, Wenjie & Liu, Sifeng & Tao, Liangyan & Cao, Yingsai & Fang, Zhigeng, 2019. "Reliability variation of multi-state components with inertial effect of deteriorating output performances," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 176-185.
    3. Aslett, Louis J.M. & Nagapetyan, Tigran & Vollmer, Sebastian J., 2017. "Multilevel Monte Carlo for Reliability Theory," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 188-196.
    4. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    5. Izquierdo, J. & Crespo Márquez, A. & Uribetxebarria, J., 2019. "Dynamic artificial neural network-based reliability considering operational context of assets," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 483-493.
    6. Peng, Rui & Xiao, Hui & Liu, Hanlin, 2017. "Reliability of multi-state systems with a performance sharing group of limited size," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 164-170.
    7. Ferdinando Chiacchio & Fabio Famoso & Diego D’Urso & Sebastian Brusca & Jose Ignacio Aizpurua & Luca Cedola, 2018. "Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model," Energies, MDPI, vol. 11(2), pages 1-22, January.
    8. Vasilyev, A. & Andrews, J. & Dunnett, S.J. & Jackson, L.M., 2021. "Dynamic Reliability Assessment of PEM Fuel Cell Systems," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    9. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    10. Raoni, Rafael & Secchi, Argimiro R., 2019. "Procedures to model and solve probabilistic dynamic system problems," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    11. Dong, Zhe & Li, Bowen & Li, Junyi & Huang, Xiaojin & Zhang, Zuoyi, 2022. "Online reliability assessment of energy systems based on a high-order extended-state-observer with application to nuclear reactors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    12. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    13. Chiacchio, Ferdinando & Iacono, Alessandra & Compagno, Lucio & D'Urso, Diego, 2020. "A general framework for dependability modelling coupling discrete-event and time-driven simulation," Reliability Engineering and System Safety, Elsevier, vol. 199(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.
    2. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.
    3. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    4. Ferdinando Chiacchio & Fabio Famoso & Diego D’Urso & Sebastian Brusca & Jose Ignacio Aizpurua & Luca Cedola, 2018. "Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model," Energies, MDPI, vol. 11(2), pages 1-22, January.
    5. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    6. Michele Compare & Francesco Di Maio & Enrico Zio & Fausto Carlevaro & Sara Mattafirri, 2016. "Improving scheduled maintenance by missing data reconstruction: A double-loop Monte Carlo approach," Journal of Risk and Reliability, , vol. 230(5), pages 502-511, October.
    7. Di Maio, Francesco & Pettorossi, Chiara & Zio, Enrico, 2023. "Entropy-driven Monte Carlo simulation method for approximating the survival signature of complex infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    8. Wang, Fan & Li, Heng, 2018. "System reliability under prescribed marginals and correlations: Are we correct about the effect of correlations?," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 94-104.
    9. Tito G. Amaral & Vitor Fernão Pires & Armando Cordeiro & Daniel Foito & João F. Martins & Julia Yamnenko & Tetyana Tereschenko & Liudmyla Laikova & Ihor Fedin, 2023. "Incipient Fault Diagnosis of a Grid-Connected T-Type Multilevel Inverter Using Multilayer Perceptron and Walsh Transform," Energies, MDPI, vol. 16(6), pages 1-18, March.
    10. Penttinen, Jussi-Pekka & Niemi, Arto & Gutleber, Johannes & Koskinen, Kari T. & Coatanéa, Eric & Laitinen, Jouko, 2019. "An open modelling approach for availability and reliability of systems," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 387-399.
    11. Rocco, Claudio M. & Moronta, José & Ramirez-Marquez, José E. & Barker, Kash, 2017. "Effects of multi-state links in network community detection," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 46-56.
    12. Compare, Michele & Bellani, Luca & Zio, Enrico, 2017. "Reliability model of a component equipped with PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 4-11.
    13. Shiyu Chen & Wei Wang & Enrico Zio, 2021. "A Simulation-Based Multi-Objective Optimization Framework for the Production Planning in Energy Supply Chains," Energies, MDPI, vol. 14(9), pages 1-27, May.
    14. Kim, Hyeonmin & Kim, Jung Taek & Heo, Gyunyoung, 2018. "Failure rate updates using condition-based prognostics in probabilistic safety assessments," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 225-233.
    15. Martin Folch-Calvo & Francisco Brocal-Fernández & Cristina González-Gaya & Miguel A. Sebastián, 2020. "Analysis and Characterization of Risk Methodologies Applied to Industrial Parks," Sustainability, MDPI, vol. 12(18), pages 1-35, September.
    16. Cadini, F. & Gioletta, A., 2016. "A Bayesian Monte Carlo-based algorithm for the estimation of small failure probabilities of systems affected by uncertainties," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 15-27.
    17. Turati, Pietro & Pedroni, Nicola & Zio, Enrico, 2016. "Advanced RESTART method for the estimation of the probability of failure of highly reliable hybrid dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 117-126.
    18. Sergio Copiello, 2020. "Business as Usual with Article Processing Charges in the Transition towards OA Publishing: A Case Study Based on Elsevier," Publications, MDPI, vol. 8(1), pages 1-14, January.
    19. Shafiee, Mahmood & Finkelstein, Maxim & Bérenguer, Christophe, 2015. "An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 463-471.
    20. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:149:y:2016:i:c:p:1-13. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.