IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v8y2017i2d10.1007_s13198-016-0480-9.html
   My bibliography  Save this article

Exploration of reliability algorithms using modified Weibull distribution: application on gas turbine

Author

Listed:
  • Ahmed Zohair Djeddi

    (University of Djelfa)

  • Ahmed Hafaifa

    (University of Djelfa)

  • Abdellah Kouzou

    (University of Djelfa)

  • Salam Abudura

    (University of Medea)

Abstract

The main purpose of the present paper is the exploration of an algorithm for reliability assessment and analysis based on the modified Weibull distribution. Indeed, an original methodology for the monitoring and the evaluation of the a gas turbine system reliability has been proposed and set up. The obtained results in this work show the effectiveness of the used approach for assessing the operational reliability (observed and estimated) for the studied system by providing advantageous performance in minimizing the number of data classes. On the other side; these results allow a better understanding of the studied system behavior based on its reliability and survival function analyzing. Finally, the validation tests on heavily biased data and on incomplete data confirm the effectiveness of the proposed algorithm.

Suggested Citation

  • Ahmed Zohair Djeddi & Ahmed Hafaifa & Abdellah Kouzou & Salam Abudura, 2017. "Exploration of reliability algorithms using modified Weibull distribution: application on gas turbine," 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 1885-1894, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-016-0480-9
    DOI: 10.1007/s13198-016-0480-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-016-0480-9
    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/s13198-016-0480-9?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. Zhu, Shun-Peng & Huang, Hong-Zhong & Peng, Weiwen & Wang, Hai-Kun & Mahadevan, Sankaran, 2016. "Probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 146(C), pages 1-12.
    2. Zare, V., 2016. "Exergoeconomic analysis with reliability and availability considerations of a nuclear energy-based combined cycle power plant," Energy, Elsevier, vol. 96(C), pages 187-196.
    3. Saralees Nadarajah & Gauss Cordeiro & Edwin Ortega, 2013. "The exponentiated Weibull distribution: a survey," Statistical Papers, Springer, vol. 54(3), pages 839-877, August.
    4. Shmueli, Galit & Jank, Wolfgang & Hyde, Valerie, 2008. "Transformations for semi-continuous data," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4000-4020, April.
    5. Tsoutsanis, Elias & Meskin, Nader & Benammar, Mohieddine & Khorasani, Khashayar, 2016. "A dynamic prognosis scheme for flexible operation of gas turbines," Applied Energy, Elsevier, vol. 164(C), pages 686-701.
    6. Sarhan, Ammar M. & Apaloo, Joseph, 2013. "Exponentiated modified Weibull extension distribution," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 137-144.
    7. Hasumi, Tomohiro & Akimoto, Takuma & Aizawa, Yoji, 2009. "The Weibull–log Weibull distribution for interoccurrence times of earthquakes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(4), pages 491-498.
    8. Yang, Jingjing & Scott, David W., 2013. "Robust fitting of a Weibull model with optional censoring," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 149-161.
    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. Li, Xiao-Yang & Chen, Wen-Bin & Kang, Rui, 2021. "Performance margin-based reliability analysis for aircraft lock mechanism considering multi-source uncertainties and wear," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    2. Fang, Longxiang & Zhang, Xinsheng, 2015. "Stochastic comparisons of parallel systems with exponentiated Weibull components," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 25-31.
    3. Mehrabian, M.J. & Khoshgoftar Manesh, M.H., 2023. "4E, risk, diagnosis, and availability evaluation for optimal design of a novel biomass-solar-wind driven polygeneration system," Renewable Energy, Elsevier, vol. 219(P2).
    4. Rasool Roozegar & Saralees Nadarajah & Eisa Mahmoudi, 2022. "The Power Series Exponential Power Series Distributions with Applications to Failure Data Sets," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 44-78, May.
    5. Chen, Yu-Zhi & Tsoutsanis, Elias & Xiang, Heng-Chao & Li, Yi-Guang & Zhao, Jun-Jie, 2022. "A dynamic performance diagnostic method applied to hydrogen powered aero engines operating under transient conditions," Applied Energy, Elsevier, vol. 317(C).
    6. J. Wang, 2016. "Reviews of seismicity around Taiwan: Weibull distribution," 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 1651-1668, February.
    7. Liu, Xintian & Mao, Kui & Wang, Xiaolan & Wang, Xu & Wang, Yansong, 2020. "A modified quality loss model of service life prediction for products via wear regularity," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    8. Zhongzhe Chen & Shuchen Cao & Zijian Mao, 2017. "Remaining Useful Life Estimation of Aircraft Engines Using a Modified Similarity and Supporting Vector Machine (SVM) Approach," Energies, MDPI, vol. 11(1), pages 1-14, December.
    9. Mohammad Ali Farsi & S. Masood Hosseini, 2019. "Statistical distributions comparison for remaining useful life prediction of components via ANN," 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(3), pages 429-436, June.
    10. Rong Yuan & Debiao Meng & Haiqing Li, 2016. "Multidisciplinary reliability design optimization using an enhanced saddlepoint approximation in the framework of sequential optimization and reliability analysis," Journal of Risk and Reliability, , vol. 230(6), pages 570-578, December.
    11. Kang, Do Won & Kim, Tong Seop, 2018. "Model-based performance diagnostics of heavy-duty gas turbines using compressor map adaptation," Applied Energy, Elsevier, vol. 212(C), pages 1345-1359.
    12. Bui, Ha & Sakurahara, Tatsuya & Pence, Justin & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 405-428.
    13. Zhang, Wei & Li, Xiang & Ma, Hui & Luo, Zhong & Li, Xu, 2021. "Transfer learning using deep representation regularization in remaining useful life prediction across operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    14. Hazhir Homei & Saralees Nadarajah, 2018. "On Products and Mixed Sums of Gamma and Beta Random Variables Motivated by Availability," Methodology and Computing in Applied Probability, Springer, vol. 20(2), pages 799-810, June.
    15. Hajialigol, Najmeh & Fattahi, Abolfazl & Karimi, Nader & Jamali, Mostafa & Keighobadi, Shervin, 2024. "Hybridized power-hydrogen generation using various configurations of Brayton-organic flash Rankine cycles fed by a sustainable fuel: Exergy and exergoeconomic analyses with ANN prediction," Energy, Elsevier, vol. 290(C).
    16. Ghaffarpour, Reza & Mozafari, Babak & Ranjbar, Ali Mohammad & Torabi, Taghi, 2018. "Resilience oriented water and energy hub scheduling considering maintenance constraint," Energy, Elsevier, vol. 158(C), pages 1092-1104.
    17. Wedad Elmaghraby & Wolfgang Jank & Shu Zhang & Itir Z. Karaesmen, 2015. "Sales Force Behavior, Pricing Information, and Pricing Decisions," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 495-510, October.
    18. Jesse G. Wales & Alexander J. Zolan & William T. Hamilton & Alexandra M. Newman & Michael J. Wagner, 2023. "Combining simulation and optimization to derive operating policies for a concentrating solar power plant," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 119-150, March.
    19. Shakhawat Hossain & Shahedul A. Khan, 2020. "Shrinkage estimation of the exponentiated Weibull regression model for time‐to‐event data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(4), pages 592-610, November.
    20. Barmalzan, Ghobad & Najafabadi, Amir T. Payandeh & Balakrishnan, Narayanaswamy, 2015. "Stochastic comparison of aggregate claim amounts between two heterogeneous portfolios and its applications," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 235-241.

    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_s13198-016-0480-9. 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.