Academic Journal of Engineering and Technology Science, 2024, 7(1); doi: 10.25236/AJETS.2024.070111.
Wei Yu
Air China Limited, Engineering Maintenance Department, Beijing, 101312, China
Reliability management is one of the basic work to protect the safety of civil aviation. At present, more and more domestic passenger planes are invested, but due to the low availability of data and limited number of aircraft, there are few studies on reliability management of domestic civil aviation aircraft. In this paper, the three-parameter Weibull distribution is used to analyze the small sample problem, and Take reliability management of pitot tube of domestic ARJ21 fleet as the research object, and the application of Weibull in the reliability management optimization of civil aviation aircraft engineering is explored.
Reliability management; Weibull analysis; Civil aviation
Wei Yu. Application of Weibull Analysis in the Optimization of Civil Aviation Aircraft Engineering Reliability Management. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 1: 68-73. https://doi.org/10.25236/AJETS.2024.070111.
[1] Xiaoping Li, Duo Xu, Tao J. Application and reflection of reliability management in aero-engine development [J]. Gas Turbine Experiment and Research, 2018.
[2] Kohout J. Three-parameter Weibull distribution with upper limit applicable in reliability studies and materials testing[J].Microelectronics and reliability, 2022.
[3] Zhang Y, Cao K, Dong W. Research on improvement and optimisation of modelling method of China's civil aircraft market demand forecast model[J].The Aeronautical journal, 2021 (Jul. TN.1289): 125.
[4] Muse A H. Bayesian Inference Of The Generalized Log-Logistic Accelerated Failure Time Model For Censored Survival Data [C]// II. International Conference on Mathematics and its applications in science and engineering (ICMASE 2021). 2021.
[5] Jia X. Reliability analysis for Weibull distribution with homogeneous heavily censored data based on Bayesian and least-squares methods [J]. Applied Mathematical Modelling, 2020. DOI:10. 1016/j. apm. 2020.02.013.