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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
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    References listed on IDEAS

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    1. Shmueli, Galit & Jank, Wolfgang & Hyde, Valerie, 2008. "Transformations for semi-continuous data," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4000-4020, April.
    2. 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.
    3. Sarhan, Ammar M. & Apaloo, Joseph, 2013. "Exponentiated modified Weibull extension distribution," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 137-144.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Saralees Nadarajah & Gauss Cordeiro & Edwin Ortega, 2013. "The exponentiated Weibull distribution: a survey," Statistical Papers, Springer, vol. 54(3), pages 839-877, August.
    Full references (including those not matched with items on IDEAS)

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