IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v138y2015icp13-20.html
   My bibliography  Save this article

Assessing the reliability of components with micro- and nano-structures when they are part a multi-scale system

Author

Listed:
  • Ebrahimi, Nader
  • Shehadeh, Mahmoud

Abstract

Products with macro- and meso-scales components have grown into multi-scale systems where some of their components have shrunk to a smaller scale such as micro- and nano-structures. In practice, engineers may be unable to accurately assess their designs to improve the reliability of components in multi-scale systems, because component parts with micro- and nano-structures cannot be realized directly in system design phase. Thus, all kinds of design processes such as engineering verifications for physics or functions become increasingly complex in a muti-scale system. For this shortcoming, we present a parametric Bayesian method that enables engineers to assess indirectly the reliability and the quality of a component with either a micro-structure or a nano-structure using experimental data on failure time of the multi-scale system. Our proposed Bayesian approach is flexible in allowing a general model for distributions of failure times of a multi-scale system and its components. Our method is applied to a simulated data set.

Suggested Citation

  • Ebrahimi, Nader & Shehadeh, Mahmoud, 2015. "Assessing the reliability of components with micro- and nano-structures when they are part a multi-scale system," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 13-20.
  • Handle: RePEc:eee:reensy:v:138:y:2015:i:c:p:13-20
    DOI: 10.1016/j.ress.2015.01.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015000253
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2015.01.015?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. Qiqing Yu & Jiahui Li, 2012. "THE NPMLE of the joint distribution function with right-censored and masked competing risks data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 753-764.
    2. Bensi, Michelle & Kiureghian, Armen Der & Straub, Daniel, 2013. "Efficient Bayesian network modeling of systems," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 200-213.
    3. Bocchetti, D. & Giorgio, M. & Guida, M. & Pulcini, G., 2009. "A competing risk model for the reliability of cylinder liners in marine Diesel engines," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1299-1307.
    4. Der Kiureghian, Armen & Song, Junho, 2008. "Multi-scale reliability analysis and updating of complex systems by use of linear programming," Reliability Engineering and System Safety, Elsevier, vol. 93(2), pages 288-297.
    5. Yu, Qiqing & Qin, Hao & Wang, Jiaping, 2010. "About conditional masking probability models," Statistics & Probability Letters, Elsevier, vol. 80(15-16), pages 1174-1179, August.
    6. Sarhan, Ammar M. & Hamilton, David C. & Smith, B., 2010. "Statistical analysis of competing risks models," Reliability Engineering and System Safety, Elsevier, vol. 95(9), pages 953-962.
    7. Salazar, Daniel & Rocco, Claudio M. & Galván, Blas J., 2006. "Optimization of constrained multiple-objective reliability problems using evolutionary algorithms," Reliability Engineering and System Safety, Elsevier, vol. 91(9), pages 1057-1070.
    Full references (including those not matched with items on IDEAS)

    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. Coolen-Maturi, Tahani & Coolen, Frank P.A., 2014. "Nonparametric predictive inference for combined competing risks data," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 87-97.
    2. Tien, Iris & Der Kiureghian, Armen, 2016. "Algorithms for Bayesian network modeling and reliability assessment of infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 134-147.
    3. Izquierdo, J. & Márquez, A. Crespo & Uribetxebarria, J. & Erguido, A., 2020. "On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects," Renewable Energy, Elsevier, vol. 153(C), pages 1100-1110.
    4. Wang, Chaonan & Xing, Liudong & Levitin, Gregory, 2013. "Reliability analysis of multi-trigger binary systems subject to competing failures," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 9-17.
    5. Cao, Dingzhou & Murat, Alper & Chinnam, Ratna Babu, 2013. "Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 154-163.
    6. Rodríguez, Joanna & Lillo, Rosa E. & Ramírez-Cobo, Pepa, 2015. "Failure modeling of an electrical N-component framework by the non-stationary Markovian arrival process," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 126-133.
    7. Jing Tian & Dedi Liu & Shenglian Guo & Zhengke Pan & Xingjun Hong, 2019. "Impacts of Inter-Basin Water Transfer Projects on Optimal Water Resources Allocation in the Hanjiang River Basin, China," Sustainability, MDPI, vol. 11(7), pages 1-19, April.
    8. Ghafory-Ashtiany, Mohsen & Arghavani, Mahban, 2022. "Physical performance of power grids against earthquakes: from framework to implementation," International Journal of Critical Infrastructure Protection, Elsevier, vol. 39(C).
    9. Mrinal Kanti Sen & Subhrajit Dutta & Golam Kabir, 2021. "Flood Resilience of Housing Infrastructure Modeling and Quantification Using a Bayesian Belief Network," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    10. Wang, Chaonan & Xing, Liudong & Peng, Rui & Pan, Zhusheng, 2017. "Competing failure analysis in phased-mission systems with multiple functional dependence groups," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 24-33.
    11. Cook, Jason L. & Ramirez-Marquez, Jose Emmanuel, 2009. "Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 218-228.
    12. Bibartiu, Otto & Dürr, Frank & Rothermel, Kurt & Ottenwälder, Beate & Grau, Andreas, 2021. "Scalable k-out-of-n models for dependability analysis with Bayesian networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    13. Adumene, Sidum & Khan, Faisal & Adedigba, Sunday & Zendehboudi, Sohrab & Shiri, Hodjat, 2021. "Dynamic risk analysis of marine and offshore systems suffering microbial induced stochastic degradation," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    14. Zhaojun Yang & Xiaoxu Li & Chuanhai Chen & Hongxun Zhao & Dingyu Yang & Jinyan Guo & Wei Luo, 2019. "Reliability assessment of the spindle systems with a competing risk model," Journal of Risk and Reliability, , vol. 233(2), pages 226-234, April.
    15. Coolen-Maturi, Tahani, 2014. "Nonparametric predictive pairwise comparison with competing risks," Reliability Engineering and System Safety, Elsevier, vol. 132(C), pages 146-153.
    16. Fang, Chen & Cui, Lirong, 2021. "Balanced Systems by Considering Multi-state Competing Risks Under Degradation Processes," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    17. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2021. "A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    18. Bensi, Michelle & Kiureghian, Armen Der & Straub, Daniel, 2013. "Efficient Bayesian network modeling of systems," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 200-213.
    19. Safari, Jalal, 2012. "Multi-objective reliability optimization of series-parallel systems with a choice of redundancy strategies," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 10-20.
    20. Attar, Ahmad & Raissi, Sadigh & Khalili-Damghani, Kaveh, 2017. "A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 177-191.

    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:138:y:2015:i:c:p:13-20. 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.