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System Maintainability Estimation with Multi-Peak Time Distribution based on the Bayesian Melding Method Cover

System Maintainability Estimation with Multi-Peak Time Distribution based on the Bayesian Melding Method

By: Mochao Pei,  Jianping Hao and  Cuijuan Gao  
Open Access
|Jun 2025

References

  1. Luo, X., Ge, Z., Zhang, S., Yang, Y. (2021). A method for the maintainability evaluation at design stage using maintainability design attributes. Reliability Engineering & System Safety, 210, 107535. https://doi.org/10.1016/j.ress.2021.107535
  2. Dement, A. C., Hartman, R. D. (1986). Operational suitability evaluation of a tactical fighter system. In 3rd Flight Testing Conference and Technical Display. Reston, Virigina: American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.1986-9753
  3. Danjuma, M. U., Yusuf, B., Yusuf, I. (2022). Reliability, availability, maintainability, and dependability analysis of cold standby series-parallel system. Journal of Computational and Cognitive Engineering, 1 (4), 193–200. https://doi.org/10.47852/bonviewJCCE2202144
  4. Wu, Z., Hao, J. (2020). A maintenance task similarity‐based prior elicitation method for Bayesian maintainability demonstration. Mathematical Problems in Engineering. https://doi.org/10.1155/2020/2730691
  5. Zellner, A. (2002). Information processing and Bayesian analysis. Journal of Econometrics, 107 (1–2), 41–50. https://doi.org/10.1016/s0304-4076(01)00112-9
  6. Ibrahim, J. G., Chen, M.-H., Sinha, D. (2003). On optimality properties of the power prior. Journal of the American Statistical Association, 98 (461), 204–213. https://doi.org/10.1198/016214503388619229
  7. Zhou, C., Xu, D., Wang, X. (2021). A small-sample test method for equipment maintainability verification under mixed pre-test distribution. Electronics Optics & Control, 28 (4), 73–76. https://doi.org/10.3969/j.issn.1671-637X.2021.04.016
  8. Guo, J., Li, Z., Jin, J. (2018). System reliability assessment with multilevel information using the Bayesian melding method. Reliability Engineering & System Safety, 170, 146–158. https://doi.org/10.1016/j.ress.2017.09.020
  9. Yang, L., He, K., Guo, Y. (2018). A novel Bayesian melding approach for reliability estimation subjected to inconsistent priors and heterogeneous data sets. IEEE Access, 6, 38835–38850. https://doi.org/10.1109/ACCESS.2018.2853135
  10. Liu, B., Wang, J. (2013). Compatibility check of the prior information on low voltage switchgear. Applied Mechanics and Materials, 330, 830–833. https://doi.org/10.4028/www.scientific.net/AMM.330.830
  11. Zhao, Q., Jia, X., Cheng, Z., Guo, B. (2019). Bayesian estimation of residual life for Weibull-distributed components of on-orbit satellites based on multi-source information fusion. Applied Sciences, 9 (15), 3017. https://doi.org/10.3390/app9153017
  12. Zhang, Z. (2009). Research on method which confirmed small sample maintainability verification test plan based on fitting error simulation. MS Thesis, National University of Defense Technology, Changsha, China.
  13. Zhu, Z. (2008). Research on system maintainability integration method based on Bayesian theory for panzer equipment. MS Thesis, National University of Defense Technology, Changsha, China.
  14. Wang, J. (2007). The research on maintainability demonstration method based on small sample for panzer equipment. MS Thesis, National University of Defense Technology, Changsha, China.
  15. Li, J., Chen, Y., Zhang, Y., Huang, H. (2019). Availability modeling for periodically inspection system with different lifetime and repair-time distribution. Chinese Journal of Aeronautics, 32 (7), 1667–1672. https://doi.org/10.1016/j.cja.2019.03.025
  16. International Electrotechnical Commission (IEC). (2006). Maintainability of equipment - Part 3: Verification and collection, analysis and presentation of data. IEC 60706–3:2006.
  17. Smith, D. J. (1972). Reliability Engineering. Pitman, ISBN 978-0273316596.
  18. Smith, D. J. (2021). Reliability, Maintainability and Risk: Practical Methods for Engineers. Butterworth-Heinemann, ISBN 978-0323912617.
  19. Gan, M. (1995). Design and Demonstration for Maintainability. Beijing, China: National Defense Industry Press. ISBN 978-7118014259.
  20. Knezevic, J. (1997). Systems Maintainability. Springer, ISBN 978-0412802706.
  21. Lee, P. M. (2012). Bayesian Statistics: An Introduction. Wiley, ISBN 978-1118332573.
  22. Zhao, Y.-G., Ono, T. (2001). Moment methods for structural reliability. Structural Safety, 23 (1), 47–75. https://doi.org/10.1016/S0167-4730(00)00027-8
  23. Zhang, Y.-Y., Rong, T.-Z., Li, M.-M. (2019). The empirical Bayes estimators of the mean and variance parameters of the normal distribution with a conjugate normal-inverse-gamma prior by the moment method and the MLE method. Communications in Statistics -Theory and Methods, 48 (9), 2286–2304. https://doi.org/10.1080/03610926.2018.1465081
  24. Chen, Y.-C. (2017). A tutorial on kernel density estimation and recent advances. Biostatistics & Epidemiology, 1 (1), 161–187. https://doi.org/10.1080/24709360.2017.1396742
  25. Evans, M., Moshonov, H. (2006). Checking for prior-data conflict. Bayesian Analysis, 1 (4), 893–914. https://doi.org/10.1214/06-BA129
  26. Ahmad, A., Ahmad, S. P. (2019). Weighted analogue of inverse gamma distribution: Statistical properties, estimation and simulation study. Pakistan Journal of Statistics and Operation Research, 15 (1), 25–37. https://doi.org/10.18187/pjsor.v15i1.2238
  27. Louzada, F., Ramos, P. L. (2018). Efficient closed-form maximum a posteriori estimators for the gamma distribution. Journal of Statistical Computation and Simulation, 88 (6), 1134–1146. https://doi.org/10.1080/00949655.2017.1422503
  28. Rubin, D. B. (1984). Bayesianly justifiable and relevant frequency calculations for the applied statistician. The Annals of Statistics, 12 (4), 1151–1172. https://doi.org/10.1214/aos/1176346785
  29. Liang, F. (2002). Dynamically weighted importance sampling in Monte Carlo computation. Journal of the American Statistical Association, 97 (459), 807–821. https://doi.org/10.1198/016214502388618618
Language: English
Page range: 110 - 121
Submitted on: Nov 6, 2024
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Accepted on: Apr 30, 2025
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Published on: Jun 17, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2025 Mochao Pei, Jianping Hao, Cuijuan Gao, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.