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Random effects model for the reliability management of modules of a fighter aircraft

Author

Listed:
  • Sohn, So Young
  • Yoon, Kyung Bok
  • Chang, In Sang

Abstract

The operational availability of fighter aircrafts plays an important role in the national defense. Low operational availability of fighter aircrafts can cause many problems and ROKA (Republic of Korea Airforce) needs proper strategies to improve the current practice of reliability management by accurately forecasting both MTBF (mean time between failure) and MTTR (mean time to repair). In this paper, we develop a random effects model to forecast both MTBF and MTTR of installed modules of fighter aircrafts based on their characteristics and operational conditions. Advantage of using such a random effects model is the ability of accommodating not only the individual characteristics of each module and operational conditions but also the uncertainty caused by random error that cannot be explained by them. Our study is expected to contribute to ROKA in improving operational availability of fighter aircrafts and establishing effective logistics management.

Suggested Citation

  • Sohn, So Young & Yoon, Kyung Bok & Chang, In Sang, 2006. "Random effects model for the reliability management of modules of a fighter aircraft," Reliability Engineering and System Safety, Elsevier, vol. 91(4), pages 433-437.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:4:p:433-437
    DOI: 10.1016/j.ress.2005.02.008
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    Citations

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    Cited by:

    1. S Y Sohn & Y Kim & B T Kim, 2009. "Cost of ownership model for spare engines purchase for the Korean navy acquisition program," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1674-1682, December.
    2. Freddy Hernández & Viviana Giampaoli, 2018. "The Impact of Misspecified Random Effect Distribution in a Weibull Regression Mixed Model," Stats, MDPI, vol. 1(1), pages 1-29, May.
    3. S Y Sohn & K B Yoon, 2010. "Dynamic preventive maintenance scheduling of the modules of fighter aircraft based on random effects regression model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(6), pages 974-979, June.
    4. Jeon, Jeasu & Sohn, So Young, 2015. "Product failure pattern analysis from warranty data using association rule and Weibull regression analysis: A case study," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 176-183.

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