Document Type : Research Paper


Department of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran.


In this research, multi-state complex systems are analyzed in order to measure reliability and predict residual of systems’ lifetime under the effect of an out of control noise factor. Hence, the analytic method helps us to estimate multi-state system reliability, and then means residual lifetime that is calculated under normal conditions. Finally, the calculation is updated for out of control noisy condition using the accelerated method. To reveal the applied results, the proposed policy is implemented in a case study in a molding machine on SNJ Co. at Isfahan.


Main Subjects

[1]     Das, S., & Nanda, A. K. (2013). Some stochastic orders of dynamic additive mean residual life model. Journal of statistical planning and inference143(2), 400-407.
[2]     Deloux, E., Castanier, B., Yeung, T., & Bérenguer, C. (2006, November). A Predictive Maintenance Policy Combining Statistical Process Control and Condition-Based Approaches. 31 ESReDA seminar on ageing (pp. 210-220).
[3]     Dieulle, L., Bérenguer, C., Grall, A., & Roussignol, M. (2003). Sequential condition-based maintenance scheduling for a deteriorating system. European journal of operational research150(2), 451-461.
[4]     Eryilmaz, S. (2017). Computing optimal replacement time and mean residual life in reliability shock models. Computers & industrial engineering103, 40-45.
[5]     Huang, J., & Zuo, M. J. (2004). Dominant multi-state systems. IEEE transactions on reliability53(3), 362-368.
[6]     Huang, W., Zhou, J., & Ning, J. (2016). A Condition Based Maintenance for System Subject to Competing Failure due to Degradation and Shock. International journal of applied mathematics46(2).
[7]     Kurniati, N., Yeh, R. H., & Lin, J. J. (2015). Quality inspection and maintenance: the framework of interaction. Procedia manufacturing4, 244-251.
[8]     Li, W., & Pham, H. (2005). Reliability modeling of multi-state degraded systems with multi-competing failures and random shocks. IEEE transactions on reliability54(2), 297-303.
[9]        Yingkui, G., & Jing, L. (2012). Multi-state system reliability: a new and systematic review. Procedia engineering29, 531-536.
[10]    Zhao, M., Jiang, H., & Liu, X. (2013). A note on estimation of the mean residual life function with left-truncated and right-censored data. Statistics & probability letters83(10), 2332-2336.
[11]    Madsen, H. O. (1985, May). Random fatigue crack growth and inspection. Proceeding of 4th international conference on structural safety and reliability (ICOSSAR’85). Kobe, Japan.
[12]    Wu, S., & Wang, W. (2011). Optimal inspection policy for three-state systems monitored by control charts. Applied mathematics and computation217(23), 9810-9819.