Review Articles

Statistical inference of reliability for a K-out-of-N: G system with switching failure under Poisson shocks

Fang Luo ,

School of Science, Yanshan University, Qinhuangdao, People's Republic of China

Linmin Hu ,

School of Science, Yanshan University, Qinhuangdao, People's Republic of China

linminhu@ysu.edu.cn

Yuyu Wang ,

College of Mathematical Science, Tianjin Normal University, Tianjin, People's Republic of China

Xiaoyun Yu

School of Science, Yanshan University, Qinhuangdao, People's Republic of China

Pages 195-210 | Received 06 Dec. 2023, Accepted 07 Apr. 2024, Published online: 23 Apr. 2024,
  • Abstract
  • Full Article
  • References
  • Citations

Based on the stochastic uncertainty of the system's operating environment, this research presents statistical inferences on the mean time to failure (MTTF) of a K-out-of-N: G non-repairable system model with switching failure under Poisson shocks. The standby component is switched to the operating component when an operating component fails, with a switching failure probability of p. The MTTF of the system is derived by using the Markov process theory and the Laplace transform for two cases where the shock threshold is a constant value or a random variable. The maximum likelihood estimator (MLE) of the MTTF is obtained, and based on this estimator, asymptotic confidence interval estimation and hypothesis testing are performed. Based on the setting of the basic parameter values, the MTTF under two different cases of the shock threshold is compared. The effect of each parameter on the MTTF is analyzed in numerical simulation. The effectiveness of the above statistical inference methods is also verified by numerical simulation.

References

  • Ali, A., Khaliq, S., Ali, Z., & Dey, S. (2018). Reliability estimation of s-out-of-k system for non-identical stress-strength components. Life Cycle Reliability and Safety Engineering7(1), 33–41. https://doi.org/10.1007/s41872-018-0039-7
  • Amari, S. V., & Dill, G. (2009). A new method for reliability analysis of standby systems. In 2009 Annual Reliability and Maintainability Symposium (pp. 417–422).
  • Baek, S., & Jeon, G. (2013). A k-out-of-n system reliability optimization problem with mixed redundancy. Journal of the Korean Institute of Industrial Engineers39(2), 90–98. https://doi.org/10.7232/JKIIE.2013.39.2.090
  • Barlow, R. E., & Proschan, F. (1975). Statistical theory of reliability and life testing: Probability models. Holt, Rinehart and Winston.
  • Boddu, P., & Xing, L. (2012). Redundancy allocation for k-out-of-n: G systems with mixed spare types. In 2012 Proceedings Annual Reliability and Maintainability Symposium (pp. 1–6).
  • Chien, Y. H., Ke, J. C., & Lee, S. L. (2006). Asymptotic confidence limits for performance measures of a repairable system with imperfect service station. Communication in Statistics-Simulation and Computation35(3), 813–830. https://doi.org/10.1080/03610910600716563
  • El-Sherbeny, M. S., & Elshoubary, E. (2020). Stochastic analysis of reliability indices for a redundant system under Poisson shocks. International Journal of Computer Applications176(19), 21–30. https://doi.org/10.5120/ijca2020920143
  • El-Sherbeny, M. S., & Hussien, Z. M. (2022). Reliability analysis of a two nonidentical unit parallel system with optional vacations under Poisson shocks. Mathematical Problems in Engineering2022, 2488182. https://doi.org/10.1155/2022/2488182
  • Ge, X., Sun, J., & Wu, Q. (2021). Reliability analysis for a cold standby system under stepwise Poisson shocks. Journal of Control and Decision8(1), 27–40. https://doi.org/10.1080/23307706.2019.1633961
  • Hsu, Y. L., Ke, J. C., & Liu, T. H. (2011). Standby system with general repair, reboot delay, switching failure and unreliable repair facility—A statistical standpoint. Mathematics and Computers in Simulation81(11), 2400–2413. https://doi.org/10.1016/j.matcom.2011.03.003
  • Hsu, Y. L., Ke, J. C., Liu, T. H., & Wu, C. H. (2014). Modeling of multi-server repair problem with switching failure and reboot delay and related profit analysis. Computers and Industrial Engineering69, 21–28. https://doi.org/10.1016/j.cie.2013.12.003
  • Jana, N., & Bera, S. (2022). Interval estimation of multicomponent stress-strength reliability based on inverse Weibull distribution. Mathematics and Computers in Simulation191, 95–119. https://doi.org/10.1016/j.matcom.2021.07.026
  • Kang, J., Hu, L., Peng, R., Li, Y., & Tian, R. (2023). Availability and cost-benefit evaluation for a repairable retrial system with warm standbys and priority. Statistical Theory and Related Fields7(2), 164–175. https://doi.org/10.1080/24754269.2022.2152591
  • Ke, J. B., Lee, W. C., & Ke, J. C. (2008). Reliability-based measure for a system with standbys subjected to switching failures. Engineering Computations25(7), 694–706. https://doi.org/10.1108/02644400810899979
  • Ke, J. C., Chang, C. J., & Lee, W. C. (2018). An availability-based system with general repair via Bayesian aspect. Mathematics and Computers in Simulation144, 247–265. https://doi.org/10.1016/j.matcom.2017.09.001
  • Ke, J. C., Liu, T. H., & Yang, D. Y. (2016). Machine repairing systems with standby switching failure. Computers and Industrial Engineering99, 223–228. https://doi.org/10.1016/j.cie.2016.07.016
  • Kızılaslan, F. (2018). Classical and Bayesian estimation of reliability in a multicomponent stress–strength model based on a general class of inverse exponentiated distributions. Statistical Papers59(3), 1161–1192. https://doi.org/10.1007/s00362-016-0810-7
  • Lewis, E. (1996). Introduction to reliability engineering (2nd ed.) John Wiley & Sons.
  • Liu, T. H., Huang, Y. L., Lin, Y. B., & Chang, F. M. (2022). Cost-benefit analysis of a standby retrial system with an unreliable server and switching failure. Computation10(4), 48–64. https://doi.org/10.3390/computation10040048
  • Patawa, R., Pundir, P. S., Sigh, A. K., & Singh, A. (2022). Some inferences on reliability measures of two-non-identical units cold standby system waiting for repair. International Journal of System Assurance Engineering Management13, 172–188.
  • Pham, H., & Pham, M. (1991). Optimal designs of (k, n-k+1)-out-of-n: F system (subject to 2 failure modes) optimal designs of (k, n-k+1)-out-of-n: F system (subject to 2 failure modes). IEEE Transactions on Reliability40(5), 559–562. https://doi.org/10.1109/24.106777
  • Rasekhi, M., Saber, M. M., & Yousof, H. M. (2020). Bayesian and classical inference of reliability in multicomponent stress-strength under the generalized logistic model. Communications in Statistics-Theory and Methods50(21), 5114–5125. https://doi.org/10.1080/03610926.2020.1726958
  • Shanthikumar, J. G., & Sumita, U. (1983). General shock models associated with correlated renewal sequences. Journal of Applied Probability20(3), 600–614. https://doi.org/10.2307/3213896
  • Shanthikumar, J. G., & Sumita, U. (1984). Distribution properties of the system failure time in a general shock model. Advances in Applied Probability16(2), 363–377. https://doi.org/10.2307/1427074
  • She, J., & Pecht, M. G. (1992). Reliability of a k-out-of-n warm-standby system. IEEE Transactions on Reliability41(1), 72–75. https://doi.org/10.1109/24.126674
  • Shekhar, C., Kumar, N., Gupta, A., Kumar, A., & Varshney, S. (2020). Warm-spare provisioning computing network with switching failure, common cause failure, vacation interruption, and synchronized reneging. Reliability Engineering and System Safety199, 106910. https://doi.org/10.1016/j.ress.2020.106910
  • Wang, K. H., & Chen, Y. J. (2009). Comparative analysis of availability between three systems with general repair times, reboot delay and switching failures. Applied Mathematics and Computation215(1), 384–394. https://doi.org/10.1016/j.amc.2009.05.023
  • Wang, L., Wu, K., Tripathi, Y. M., & Lodhi, C. (2020). Reliability analysis of multicomponent stress–strength reliability from a bathtub-shaped distribution. Journal of Applied Statistics49(1), 122–142. https://doi.org/10.1080/02664763.2020.1803808
  • Wu, Q. (2012). Reliability analysis of a cold standby system attacked by shocks. Applied Mathematics and Computation218(23), 11654–11673. https://doi.org/10.1016/j.amc.2012.05.051
  • Wu, Q., & Wu, S. (2011). Reliability analysis of two-unit cold standby repairable systems under Poisson shocks. Applied Mathematics and Computation218(1), 171–182. https://doi.org/10.1016/j.amc.2011.05.089
  • Wu, Q., Zhang, J., & Tang, J. (2015). Reliability evaluation for a class of multi-unit cold standby systems under Poisson shocks. Communications in Statistics-Theory and Methods44(15), 3278–3288. https://doi.org/10.1080/03610926.2013.851232
  • Yang, D. Y., & Wu, C. H. (2021). Evaluation of the availability and reliability of a standby repairable system incorporating imperfect switchovers and working breakdowns. Reliability Engineering and System Safety207, 107366. https://doi.org/10.1016/j.ress.2020.10736

To cite this article: Fang Luo, Linmin Hu, Yuyu Wang & Xiaoyun Yu (23 Apr 2024): Statistical inference of reliability for a K-out-of-N: G system with switching failure under Poisson shocks, Statistical Theory and Related Fields, DOI: 10.1080/24754269.2024.2341982

To link to this article: https://doi.org/10.1080/24754269.2024.2341982