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Dynamic Reliability Maintenance for Complex Systems using the Survival Signature

Volume 15, Number 5, May 2019, pp. 1343-1351
DOI: 10.23940/ijpe.19.05.p10.13431351

Jiaojiao Guo and Hailin Feng

School of Mathematics and Statistics, Xidian University, Shaanxi, Xi'an, 710071, China

(Submitted on December 10, 2018; Revised on January 12, 2019; Accepted on February 8, 2019)


This paper gives a system dynamic reliability maintenance that jointly considers the system residual life and relative importance. Firstly, the component failure time of the system is generated by a Weibull model with unknown shape and scale parameters, and then the two unknown parameters are updated based on the Bayesian rules. The system residual life distribution is estimated by using the theory of survival signature. A novel component relative importance is extended to identify the most critical component groups that need to be maintained. Finally, a system with two cross-linked modules is used to illustrate the usage of our research. Simulation results show that the proposed strategies are effective and convenient.


References: 23

    1. M. C. A. Older Keizer, S. D. P. Flapper, and R. H. Teunter, “Condition-based Maintenance Policies for Systems with Multiple Dependent Components: A Review,” European Journal of Operational Research, pp. 261+405-420, 2017
    2. B. Hussin, “Development of a State Prediction Model to Aid Decision Making in Condition-based Maintenance,” University of Salford, 2007
    3. R. Jiang, “Estimating Residual Life Distribution from Fractile Curves of a Condition Variable,” in Proceedings of IEEE Prognostics & System Health Management Conference, pp. 1-6, 2016
    4. J. Yang, Y. Zhao, X. J. Li, and D. Yu, “Comprehensive Evaluation of Mean Life of Complex System,” Acta Aeronautica et Astronautica Sinica, Vol. 28, No. 6, pp. 1351-1354, 2007
    5. Z. R. Yin, J. S. Li, D. Su, and Y. X. Sun, “Reliability Assessment Model of Complex System based on Bayes-Go,” Computer Engineering, Vol. 39, No. 11, pp. 276-280, 2013
    6. H. H. Gu, Y. S. Liu, J. Ye, and Y. J. Lv, “Research on Evaluation of Mean Residual Life of Complex System based on Bayes Monte Carlo Method,” Electronic Design Engineering, Vol. 19, No. 9, pp. 104-106, 2011
    7. F. Samaniego, “System Signatures and Their Applications in Engineering Reliability,” Spring, New York, 2007
    8. F. P. A. Coolen and T. Coolen-Maturi, “Generalizing the Signature to Systems with Multiple Types of Components,” Complex Systems and Dependability, Spring, Berlin, pp. 115-130, 2012
    9. F. P. A. Coolen and T. Coolen-Maturi, “The Structure Function for System Reliability as Predictive (Imprecise) Probability,” Reliability Engineering and System Safety, Vol. 154, pp. 180-187, 2016
    10. F. P. A. Coolen and T. Coolen-Maturi, “On the Structure Function and Survival Signature for System Reliability,” Safety and Reliability Society, Vol. 36, No. 2, pp. 77-87, 2016
    11. E. Patelli, F. Geng, F. P. A. Coolen, and T. Coolen-Maturi, “Simulation Methods for System Reliability using the Survival Signature,” Reliability Engineering and System Safety, Vol. 167, pp. 327-337, 2017
    12. S. Reed, “An Efficient Algorithm for Exact Computation of System and Survival Signatures using Binary Decision Diagrams,” Reliability Engineering and System Safety, Vol. 165, pp. 257-267, 2017
    13. G. Walter, L. J. M. Aslett, and F. P. A. Coolen, “Bayesian Nonparametric System Reliability using Sets of Priors,” International Journal of Approximate Reasoning, Vol. 80, pp. 67-88, 2017
    14. G. Walter and S. D. Flapper, “Condition-based Maintenance for Complex Systems based on Current Component Status and Bayesian Updating of Component Reliability,” Reliability Engineering and System Safety, Vol. 168, pp. 227-239, 2017
    15. L. J. M. Aslett, “ReliabilityTheory: Tools for Structural Reliability Analysis. R Package,” (, accessed 2016)
    16. R Core Team, “R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing,” (, accessed 2016)
    17. Z. W. Birnbaum, “On the Importance of Different Components in A Multi-Component System,” Multivariate Analysis, Vol. Ⅱ, pp. 581-592, Academic Press, New York, 1969
    18. W. Wang, J. Loman, and P. Vassiliou, “Reliability Importance of Components in a Complex System,” in Proceedings of 2004 Annual Symposium on Reliability and Maintenance (RAMS), pp. 6-11, Los Angeles, CA, USA, January 2004
    19. E. Zio and L. Podofillini, “Monte Carlo Simulation Analysis of the Effects of Different System Performance Levels on the Importance of Multi-State Components,” Reliability Engineering and System Safety, Vol. 82, No. 1, pp. 63-73, 2003
    20. E. Zio, L. Podofillini, and G. Levitin, “Estimation of the Importance Measures of Multi-State Elements by Monte Carlo Simulation,” Reliability Engineering and System Safety, Vol. 86, No. 3, pp. 191-204, 2004
    21. F. Geng, E. Patelli, M. Beer, and F. P. A. Coolen, “Imprecise System Reliability and Component Importance based on Survival Signature,” Reliability Engineering and System Safety, Vol. 150, pp. 116-125, 2016
    22. R. M. Soland, “Bayesian Analysis of the Weibull Process with Unknown Scale and Shape Parameters,” IEEE Transactions on Reliability, Vol. 18, No. 4, pp. 181-184, 1969
    23. X. D. Zhou, Y. C. Tang, and H. L. Fei, “Bayesian Statistical Analysis for Weibull Distribution Parameters under Censored Data,” Journal of Shanghai Normal University (Natural Sciences), Vol. 37, No. 1, pp. 28-34, 2008


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