IDEAS home Printed from https://ideas.repec.org/a/inm/ordeca/v9y2012i2p128-137.html
   My bibliography  Save this article

From Reliability Block Diagrams to Fault Tree Circuits

Author

Listed:
  • Debarun Bhattacharjya

    (Business Analytics and Math Sciences, IBM T.J. Watson Research Center, Yorktown Heights, New York 10598)

  • Léa A. Deleris

    (Risk Collaboratory, Smarter Cities Technology Centre, IBM Dublin Research Laboratory, Dublin, Ireland)

Abstract

Reliability block diagrams (RBDs) depict the functional relationships between components comprising a system, whereas Bayesian networks (BNs) represent probabilistic relationships between uncertain variables. Previous research has described how one can transform an RBD into a BN. In parallel, developments in the artificial intelligence literature have shown how a BN can be transformed into another graphical representation, an arithmetic circuit, which can subsequently be used for efficient inference. In this paper, we introduce a new graphical representation that we call a fault tree circuit, which is a special kind of arithmetic circuit constructed specifically for an RBD. A fault tree circuit can be constructed directly from an RBD and is more efficient than an arithmetic circuit that is compiled from the BN corresponding to that RBD. We develop several methods for fault tree circuits, highlighting how they can aid the analyst in efficient diagnosis, sensitivity analysis, and decision support for many typical reliability problems. The circuit framework can complement tools that are popular in the reliability analysis community. We use a simple pump system example to illustrate the concepts.

Suggested Citation

  • Debarun Bhattacharjya & Léa A. Deleris, 2012. "From Reliability Block Diagrams to Fault Tree Circuits," Decision Analysis, INFORMS, vol. 9(2), pages 128-137, June.
  • Handle: RePEc:inm:ordeca:v:9:y:2012:i:2:p:128-137
    DOI: 10.1287/deca.1120.0231
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/deca.1120.0231
    Download Restriction: no

    File URL: https://libkey.io/10.1287/deca.1120.0231?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
    ---><---

    References listed on IDEAS

    as
    1. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    2. Debarun Bhattacharjya & Ross D. Shachter, 2012. "Formulating Asymmetric Decision Problems as Decision Circuits," Decision Analysis, INFORMS, vol. 9(2), pages 138-145, June.
    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. Jason R. W. Merrick & Fabrizio Ruggeri & Refik Soyer & L. Robin Keller, 2012. "From the Editors---Games and Decisions in Reliability and Risk," Decision Analysis, INFORMS, vol. 9(2), pages 81-85, June.

    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. Rogerson, Ellen C. & Lambert, James H., 2012. "Prioritizing risks via several expert perspectives with application to runway safety," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 22-34.
    2. Ibsen Chivatá Cárdenas & Saad S.H. Al‐Jibouri & Johannes I.M. Halman & Frits A. van Tol, 2014. "Modeling Risk‐Related Knowledge in Tunneling Projects," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 323-339, February.
    3. Marquez, David & Neil, Martin & Fenton, Norman, 2010. "Improved reliability modeling using Bayesian networks and dynamic discretization," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 412-425.
    4. George-Williams, Hindolo & Patelli, Edoardo, 2017. "Efficient availability assessment of reconfigurable multi-state systems with interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 431-444.
    5. Vimal Vijayan & Sanjay K Chaturvedi & Ritesh Chandra, 2020. "A failure interaction model for multicomponent repairable systems," Journal of Risk and Reliability, , vol. 234(3), pages 470-486, June.
    6. Michail Cheliotis & Evangelos Boulougouris & Nikoletta L Trivyza & Gerasimos Theotokatos & George Livanos & George Mantalos & Athanasios Stubos & Emmanuel Stamatakis & Alexandros Venetsanos, 2021. "Review on the Safe Use of Ammonia Fuel Cells in the Maritime Industry," Energies, MDPI, vol. 14(11), pages 1-20, May.
    7. Borgonovo, Emanuele & Tonoli, Fabio, 2014. "Decision-network polynomials and the sensitivity of decision-support models," European Journal of Operational Research, Elsevier, vol. 239(2), pages 490-503.
    8. Iamsumang, Chonlagarn & Mosleh, Ali & Modarres, Mohammad, 2018. "Monitoring and learning algorithms for dynamic hybrid Bayesian network in on-line system health management applications," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 118-129.
    9. 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.
    10. Zhong, Shengtong & Langseth, Helge & Nielsen, Thomas Dyhre, 2014. "A classification-based approach to monitoring the safety of dynamic systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 61-71.
    11. Bandeira, Michelle Carvalho Galvão Silva Pinto & Correia, Anderson Ribeiro & Martins, Marcelo Ramos, 2018. "General model analysis of aeronautical accidents involving human and organizational factors," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 137-146.
    12. El-Awady, Ahmed & Ponnambalam, Kumaraswamy, 2021. "Integration of simulation and Markov Chains to support Bayesian Networks for probabilistic failure analysis of complex systems," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    13. Morales-Nápoles, Oswaldo & Steenbergen, Raphaël D.J.M., 2014. "Analysis of axle and vehicle load properties through Bayesian Networks based on Weigh-in-Motion data," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 153-164.
    14. Yontay, Petek & Pan, Rong, 2016. "A computational Bayesian approach to dependency assessment in system reliability," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 104-114.
    15. Thwaites, Peter A. & Smith, Jim Q., 2018. "A graphical method for simplifying Bayesian games," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 3-11.
    16. A Léger & P Weber & E Levrat & C Duval & R Farret & B Iung, 2009. "Methodological developments for probabilistic risk analyses of socio-technical systems," Journal of Risk and Reliability, , vol. 223(4), pages 313-332, December.
    17. Jason R. W. Merrick & Fabrizio Ruggeri & Refik Soyer & L. Robin Keller, 2012. "From the Editors---Games and Decisions in Reliability and Risk," Decision Analysis, INFORMS, vol. 9(2), pages 81-85, June.
    18. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    19. Andrews, John & Fecarotti, Claudia, 2017. "System design and maintenance modelling for safety in extended life operation," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 95-108.
    20. Limao Zhang & Xianguo Wu & Yawei Qin & Miroslaw J. Skibniewski & Wenli Liu, 2016. "Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 278-301, February.

    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:inm:ordeca:v:9:y:2012:i:2:p:128-137. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.