IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i19p3072-d1489723.html
   My bibliography  Save this article

Assessing the Bridge Structure’s System Reliability Utilizing the Generalized Unit Half Logistic Geometric Distribution

Author

Listed:
  • Ahlam H. Tolba

    (Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt)

  • Osama Abdulaziz Alamri

    (Department of Statistics, Faculty of Science, University of Tabuk, Tabuk 71491, Saudi Arabia)

  • Hanan Baaqeel

    (Department of Statistics, King Abdulaziz University, Jeddah 105343, Saudi Arabia)

Abstract

Reliability is now widely recognized across various industries, including manufacturing. This study investigates a system composed of five components, one of which is a bridge network. The components are assumed to follow the generalized unit half logistic geometric distribution (GUHLGD) with equal failure rates over time. The following three improvement methods are considered: reduction, cold duplication, and hot duplication. The reliability function and mean time to failure (MTTF) are employers liability equivalence factors (REFs). Additionally, the λ fractiles of both the original and enhanced systems are obtained. Numerical results illustrate the effectiveness of these techniques, with cold duplication shown to be the most effective, offering higher reliability and MTTF compared to hot duplication. The enhanced system outperforms the original system overall.

Suggested Citation

  • Ahlam H. Tolba & Osama Abdulaziz Alamri & Hanan Baaqeel, 2024. "Assessing the Bridge Structure’s System Reliability Utilizing the Generalized Unit Half Logistic Geometric Distribution," Mathematics, MDPI, vol. 12(19), pages 1-21, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:19:p:3072-:d:1489723
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/19/3072/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/19/3072/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xia, Tangbin & Si, Guojin & Shi, Guo & Zhang, Kaigan & Xi, Lifeng, 2022. "Optimal selective maintenance scheduling for series–parallel systems based on energy efficiency optimization," Applied Energy, Elsevier, vol. 314(C).
    2. Peiravi, Abdossaber & Karbasian, Mahdi & Ardakan, Mostafa Abouei & Coit, David W., 2019. "Reliability optimization of series-parallel systems with K-mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 17-28.
    3. Xu, Zhaoyi & Saleh, Joseph Homer, 2021. "Machine learning for reliability engineering and safety applications: Review of current status and future opportunities," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    4. Zhang, Long-Wen & Dang, Chao & Zhao, Yan-Gang, 2023. "An efficient method for accessing structural reliability indexes via power transformation family," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    5. Sarhan, Ammar M., 2009. "Reliability equivalence factors of a general series–parallel system," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 229-236.
    6. Zai-Wei Li & Xiao-Zhou Liu & Si-Xin Chen, 2022. "A reliability assessment approach for slab track structure based on vehicle-track dynamics and surrogate model," Journal of Risk and Reliability, , vol. 236(1), pages 79-89, February.
    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. Ahmed T. Ramadan & Osama Abdulaziz Alamri & Ahlam H. Tolba, 2024. "Reliability Assessment of Bridge Structure Using Bilal Distribution," Mathematics, MDPI, vol. 12(10), pages 1-18, May.
    2. Ardakan, Mostafa Abouei & Talkhabi, Sajjad & Juybari, Mohammad N., 2022. "Optimal activation order vs. redundancy strategies in reliability optimization problems," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    3. Pan, Yongjun & Sun, Yu & Li, Zhixiong & Gardoni, Paolo, 2023. "Machine learning approaches to estimate suspension parameters for performance degradation assessment using accurate dynamic simulations," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Li, Yuanfu & Chen, Yao & Hu, Zhenchao & Zhang, Huisheng, 2023. "Remaining useful life prediction of aero-engine enabled by fusing knowledge and deep learning models," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    5. Phan, Hieu Chi & Dhar, Ashutosh Sutra & Bui, Nang Duc, 2023. "Reliability assessment of pipelines crossing strike-slip faults considering modeling uncertainties using ANN models," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    6. Liu, Lu & Song, Xiao & Zhou, Zhetao, 2022. "Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    7. Liu, Jiale & Wang, Huan, 2024. "A brain-inspired energy-efficient Wide Spiking Residual Attention Framework for intelligent fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    8. Yuan, Zixia & Xiong, Guojiang & Fu, Xiaofan & Mohamed, Ali Wagdy, 2023. "Improving fault tolerance in diagnosing power system failures with optimal hierarchical extreme learning machine," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    9. Costa, Nahuel & Sánchez, Luciano, 2022. "Variational encoding approach for interpretable assessment of remaining useful life estimation," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    10. Wang, Weicheng & Chen, Jinglong & Zhang, Tianci & Liu, Zijun & Wang, Jun & Zhang, Xinwei & He, Shuilong, 2023. "An asymmetrical graph Siamese network for one-classanomaly detection of engine equipment with multi-source fusion," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    11. Hieu T. T. L. Pham & Mahdi Rafieizonooz & SangUk Han & Dong-Eun Lee, 2021. "Current Status and Future Directions of Deep Learning Applications for Safety Management in Construction," Sustainability, MDPI, vol. 13(24), pages 1-37, December.
    12. Bakeer, Tammam, 2023. "General partial safety factor theory for the assessment of the reliability of nonlinear structural systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    13. Wang, Chu & Dou, Manfeng & Li, Zhongliang & Outbib, Rachid & Zhao, Dongdong & Zuo, Jian & Wang, Yuanlin & Liang, Bin & Wang, Peng, 2023. "Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    14. Lewis, Austin D. & Groth, Katrina M., 2022. "Metrics for evaluating the performance of complex engineering system health monitoring models," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    15. Bo, Yimin & Bao, Minglei & Ding, Yi & Hu, Yishuang, 2024. "A DNN-based reliability evaluation method for multi-state series-parallel systems considering semi-Markov process," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    16. Zhang, Qing & Tang, Lv & Xuan, Jianping & Shi, Tielin & Li, Rui, 2023. "An uncertainty relevance metric-based domain adaptation fault diagnosis method to overcome class relevance caused confusion," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    17. Zhou, Jianxiong & Wei, Shanbi & Chai, Yi, 2021. "Using improved dynamic Bayesian networks in reliability evaluation for flexible test system of aerospace pyromechanical device products," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    18. Sharifi, Mani & Taghipour, Sharareh & Abhari, Abdolreza, 2021. "Inspection interval optimization for a k-out-of-n load sharing system under a hybrid mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    19. Alkhaleel, Basem A., 2024. "Machine learning applications in the resilience of interdependent critical infrastructure systems—A systematic literature review," International Journal of Critical Infrastructure Protection, Elsevier, vol. 44(C).
    20. Dembińska, Anna & Eryilmaz, Serkan, 2021. "Discrete time series–parallel system and its optimal configuration," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

    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:gam:jmathe:v:12:y:2024:i:19:p:3072-:d:1489723. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.