IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v226y2012i3p283-294.html
   My bibliography  Save this article

Bayesian inference with overlapping data: methodology for reliability estimation of multi-state on-demand systems

Author

Listed:
  • C Jacksonn
  • A Mosleh

Abstract

A Bayesian system reliability analysis methodology for multiple overlapping higher level data sets within complex multi-state on-demand systems is presented in this paper. Data sets are overlapping if they are drawn from the same process at the same time, with reliability data from sensors attached to a system being a prime example. Treating overlapping data as non-overlapping loses or incorrectly infers information. The approach generated in this paper is able to incorporate overlapping data from multi-state on-demand systems with a detailed understanding of the system logic represented using fault trees, reliability block diagrams or another equivalent representation. Structure functions of the system at relevant sensor locations (developed from the system logic) in terms of component states are used in conjunction with the probability of all possible system states (or all possible state vectors) to generate the likelihood function of overlapping evidence. This forms the basis of the likelihood function used in the Bayesian analysis of the overlapping data sets.

Suggested Citation

  • C Jacksonn & A Mosleh, 2012. "Bayesian inference with overlapping data: methodology for reliability estimation of multi-state on-demand systems," Journal of Risk and Reliability, , vol. 226(3), pages 283-294, June.
    • Handle: RePEc:sae:risrel:v:226:y:2012:i:3:p:283-294
    DOI: 10.1177/1748006X11424104
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X11424104
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X11424104?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. Graves, T.L. & Hamada, M.S. & Klamann, R. & Koehler, A. & Martz, H.F., 2007. "A fully Bayesian approach for combining multi-level information in multi-state fault tree quantification," Reliability Engineering and System Safety, Elsevier, vol. 92(10), pages 1476-1483.
    2. Graves, T.L. & Hamada, M.S. & Klamann, R.M. & Koehler, A.C. & Martz, H.F., 2008. "Using simultaneous higher-level and partial lower-level data in reliability assessments," Reliability Engineering and System Safety, Elsevier, vol. 93(8), pages 1273-1279.
    3. Richard E. Barlow & Alexander S. Wu, 1978. "Coherent Systems with Multi-State Components," Mathematics of Operations Research, INFORMS, vol. 3(4), pages 275-281, November.
    4. David V. Mastran, 1976. "Incorporating Component and System Test Data into the Same Assessment: A Bayesian Approach," Operations Research, INFORMS, vol. 24(3), pages 491-499, 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. Jiang, Tao & Liu, Yu, 2017. "Parameter inference for non-repairable multi-state system reliability models by multi-level observation sequences," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 3-15.
    2. Jackson, Chris & Mosleh, Ali, 2016. "Bayesian inference with overlapping data: Reliability estimation of multi-state on-demand continuous life metric systems with uncertain evidence," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 124-135.

    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. Jackson, Chris & Mosleh, Ali, 2016. "Bayesian inference with overlapping data: Reliability estimation of multi-state on-demand continuous life metric systems with uncertain evidence," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 124-135.
    2. Jackson, Chris & Mosleh, Ali, 2012. "Bayesian inference with overlapping data for systems with continuous life metrics," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 217-231.
    3. Chenxi Liu & Nan Chen & Jianing Yang, 2015. "New method for multi-state system reliability analysis based on linear algebraic representation," Journal of Risk and Reliability, , vol. 229(5), pages 469-482, October.
    4. 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.
    5. C Jackson & A Mosleh, 2012. "Downwards inference: Bayesian analysis of overlapping higher-level data sets of complex binary-state on-demand systems," Journal of Risk and Reliability, , vol. 226(2), pages 182-193, April.
    6. Wang, Lizhi & Pan, Rong & Li, Xiaoyang & Jiang, Tongmin, 2013. "A Bayesian reliability evaluation method with integrated accelerated degradation testing and field information," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 38-47.
    7. Yang, Lechang & Wang, Pidong & Wang, Qiang & Bi, Sifeng & Peng, Rui & Behrensdorf, Jasper & Beer, Michael, 2021. "Reliability analysis of a complex system with hybrid structures and multi-level dependent life metrics," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    8. Jafary, Bentolhoda & Fiondella, Lance, 2016. "A universal generating function-based multi-state system performance model subject to correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 16-27.
    9. Yan-Feng Li & Jinhua Mi & Yu Liu & Yuan-Jian Yang & Hong-Zhong Huang, 2015. "Dynamic fault tree analysis based on continuous-time Bayesian networks under fuzzy numbers," Journal of Risk and Reliability, , vol. 229(6), pages 530-541, December.
    10. Ramirez-Marquez, Jose E. & Rocco, Claudio M. & Gebre, Bethel A. & Coit, David W. & Tortorella, Michael, 2006. "New insights on multi-state component criticality and importance," Reliability Engineering and System Safety, Elsevier, vol. 91(8), pages 894-904.
    11. 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.
    12. Serkan Eryılmaz, 2011. "A new perspective to stress–strength models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 101-115, February.
    13. Tian, Zhigang & Zuo, Ming J., 2006. "Redundancy allocation for multi-state systems using physical programming and genetic algorithms," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1049-1056.
    14. Wang, Lizhi & Pan, Rong & Wang, Xiaohong & Fan, Wenhui & Xuan, Jinquan, 2017. "A Bayesian reliability evaluation method with different types of data from multiple sources," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 128-135.
    15. Coit, David W. & Zio, Enrico, 2019. "The evolution of system reliability optimization," Reliability Engineering and System Safety, Elsevier, vol. 192(C).
    16. Khaled Guerraiche & Latifa Dekhici & Eric Chatelet & Abdelkader Zeblah, 2021. "Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm," Energies, MDPI, vol. 14(13), pages 1-19, July.
    17. Kołowrocki, K. & Kwiatuszewska-Sarnecka, B., 2008. "Reliability and risk analysis of large systems with ageing components," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1821-1829.
    18. Yingchun Xu & Xiaohu Zheng & Wen Yao & Ning Wang & Xiaoqian Chen, 2021. "A sequential multi-prior integration and updating method for complex multi-level system based on Bayesian melding method," Journal of Risk and Reliability, , vol. 235(5), pages 863-876, October.
    19. Ramirez-Marquez, Jose Emmanuel & Coit, David W., 2007. "Multi-state component criticality analysis for reliability improvement in multi-state systems," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1608-1619.
    20. Anderson-Cook, Christine M. & Crowder, Stephen & Huzurbazar, Aparna V. & Lorio, John & Ringland, James & Wilson, Alyson G., 2011. "Quantifying reliability uncertainty from catastrophic and margin defects: A proof of concept," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1063-1075.

    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:sae:risrel:v:226:y:2012:i:3:p:283-294. 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: SAGE Publications (email available below). General contact details of provider: .

    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.