IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v8y2017i2d10.1007_s13198-017-0583-y.html
   My bibliography  Save this article

Failure probability analysis by employing fuzzy fault tree analysis

Author

Listed:
  • Mohammad Yazdi

    (Eastern Mediterranean University)

  • Farzaneh Nikfar

    (Shahid Tondgouyan Petrochemical Company)

  • Mahnaz Nasrabadi

    (Zahedan Branch, Islamic Azad University)

Abstract

A significant number of accidents occur every year in chemical plants because of the failure of components. In order to manage this risk, fault tree analysis (FTA), a well-known method, was employed for failure probability analysis in the mentioned field. A complete access to the failure data is vital for quantitative FTA. There is always a shortage of information for computing failure probability of the components in high-tech industries such as chemical plants. However, the failure data is not always available, thus FTA can be extended by using the fuzzy set theory to overcome this problem. Therefore, the purpose of this study was to extend fuzzy FTA by considering common cause failure and dependency between the components. In fact, the present study was designed to consider the theoretical and practical aspect of the chemical storage tank as one of the important units in chemical plants.

Suggested Citation

  • Mohammad Yazdi & Farzaneh Nikfar & Mahnaz Nasrabadi, 2017. "Failure probability analysis by employing fuzzy fault tree analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1177-1193, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-017-0583-y
    DOI: 10.1007/s13198-017-0583-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-017-0583-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-017-0583-y?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. Arman Nedjati & Bela Vizvari & Gokhan Izbirak, 2016. "Post-earthquake response by small UAV helicopters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1669-1688, February.
    2. Arman Nedjati & Bela Vizvari & Gokhan Izbirak, 2016. "Post-earthquake response by small UAV helicopters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1669-1688, February.
    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. Özgür-Ünlüakın, Demet & Türkali, Busenur & Karacaörenli, Ayşe & Çağlar Aksezer, S., 2019. "A DBN based reactive maintenance model for a complex system in thermal power plants," Reliability Engineering and System Safety, Elsevier, vol. 190(C), pages 1-1.
    2. Weiliang Qiao & Yu Liu & Xiaoxue Ma & Yang Liu, 2020. "Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network," Risk Analysis, John Wiley & Sons, vol. 40(5), pages 957-980, May.
    3. Weiliang Qiao & Yang Liu & Xiaoxue Ma & He Lan, 2021. "Cognitive Gap and Correlation of Safety-I and Safety-II: A Case of Maritime Shipping Safety Management," Sustainability, MDPI, vol. 13(10), pages 1-24, May.
    4. Özgür-Ünlüakın, Demet & Türkali, Busenur, 2021. "Evaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    5. Hamzeh Soltanali & Mehdi Khojastehpour & José Torres Farinha & José Edmundo de Almeida e Pais, 2021. "An Integrated Fuzzy Fault Tree Model with Bayesian Network-Based Maintenance Optimization of Complex Equipment in Automotive Manufacturing," Energies, MDPI, vol. 14(22), pages 1-21, November.
    6. 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.
    7. Wen Li & Yicheng Ye & Nanyan Hu & Xianhua Wang & Qihu Wang, 2019. "Real-Time Warning and Risk Assessment of Tailings Dam Disaster Status Based on Dynamic Hierarchy-Grey Relation Analysis," Complexity, Hindawi, vol. 2019, pages 1-14, April.
    8. Varsha Sehgal & Naval Garg & Jagvinder Singh, 2023. "Impact of sustainability reporting and performance on organization legitimacy," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 143-153, March.

    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. Mahmoud Golabi & Seyed Mahdi Shavarani & Gokhan Izbirak, 2017. "An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case study of Tehran earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(3), pages 1545-1565, July.
    2. Jeong, Ho Young & Yu, David J. & Min, Byung-Cheol & Lee, Seokcheon, 2020. "The humanitarian flying warehouse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    3. Farzaneh, Mohammad Amin & Rezapour, Shabnam & Baghaian, Atefe & Amini, M. Hadi, 2023. "An integrative framework for coordination of damage assessment, road restoration, and relief distribution in disasters," Omega, Elsevier, vol. 115(C).
    4. Ilić, Damir & Milošević, Isidora & Ilić-Kosanović, Tatjana, 2022. "Application of Unmanned Aircraft Systems for smart city transformation: Case study Belgrade," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    5. Mohammad Yazdi, 2019. "A review paper to examine the validity of Bayesian network to build rational consensus in subjective probabilistic failure analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(1), pages 1-18, February.
    6. Josip Marić & Carlos Galera-Zarco & Marco Opazo-Basáez, 2022. "The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1003-1044, December.
    7. Sabir, Muhammad & Marwan, Muhammad & Ahmad, Salman & Fiaz, Muhammad & Khan, Farhan, 2020. "Observer and descriptor satisfying incremental quadratic constraint for class of chaotic systems and its applications in a quadrotor chaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    8. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.

    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:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-017-0583-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.