A Novel Algorithm for Estimating Reliability of Ready-to-use Systems in Designing Phase for Designed Lifetime Based on Markov Method and Fuzzy Approach

Document Type : Research Paper

Authors

Department of industrial engineering, Faculty of engineering, Kharazmi University, Tehran, Iran

Abstract

Reliability is one of the most important factors of complex systems which play a crucial role in performance of modern systems. In this study, a novel algorithm for estimating reliability of ready-to-use systems in designing phase for designed lifetime is proposed. At first stage, the related studies are checked, and then fundamental theories of each section are presented. According to the particular structure of ready-to-use systems and Markov Chain conditions, a new model based on Markov method and Fuzzy approach is suggested. The performance of proposed model is validated by testing on a real system. Therefore, the reliability and mean time to failure of the industrial system is estimated by the algorithm. Finally, practical suggestions are recommended for optimizing the system reliability.

Keywords

Main Subjects


Billinton, R., and Allan, R. N. (1992). Reliability evaluation of engineering systems. New York: Plenum press.
Bobbio, A., Portinale, L., Minichino, M., and Ciancamerla, E. (2001). Improving the analysis of dependable systems by mapping fault trees into Bayesian networks. Reliability Engineering & System Safety, Vol. 71(3), pp. 249–260.
Bucci, P., Kirschenbaum, J., Mangan, L. A., Aldemir, T., Smith, C., and Wood, T. (2008). Construction of event-tree/fault-tree models from a Markov approach to dynamic system reliability. Reliability Engineering & System Safety, Vol. 93(11), pp. 1616–1627.
Clemens, P.L., Fault Tree Analysis, Fourth Edition, Lecture Presentation, Sverdrup Technology, Inc (1992).
Dominguez-Garcia, A. D., Kassakian, J. G., Schindall, J. E., and Zinchuk, J. J. (2008). An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems. Reliability Engineering & System Safety, Vol. 93(11), pp. 1628–1649.
Jianzhong, Y., and Julian, Z. (2011). Application Research of Markov in Flight Control System Safety Analysis. Procedia Engineering, Vol. 17, pp. 515–520.
Kharazmi, O., and Saadatinik, A. (2016). Hyperbolic Cosine-F Family of Distributions with an Application to Exponential Distribution. Gazi University Journal of Science, Vol. 29(4), pp. 811-829.
Kharazmi, O. (2017). Hyperbolic Cosine–Exponentiated Exponential Lifetime Distribution and its Application in Reliability. International Journal of Supply and Operations Management, Vol. 4(1), pp. 63-77.
Levitin, G., Jia, H., Ding, Y., Song, Y., and Dai, Y. (2017). Reliability of multi-state systems with free access to repairable standby elements. Reliability Engineering & System Safety, Vol. 167, pp. 192-197.
Li, Y., Cui, L., and Lin, C. (2017). Modeling and analysis for multi-state systems with discrete-time Markov regime- switching. Reliability Engineering & System Safety, Vol. 166, pp. 41-49.
Lu, J.-M., and Wu, X.-Y. (2014). Reliability evaluation of generalized phased-mission systems with repairable components. Reliability Engineering & System Safety, Vol. 121, pp. 136–145.
Manesh, M. K., Rad, M. P., and Rosen, M. A. (2018). New procedure for determination of availability and reliability of complex cogeneration systems by improving the approximated Markov method. Applied Thermal Engineering. Vol. 138, pp. 62-71.
Ross, S. M. (2014). Introduction to probability and statistics for engineers and scientists. Academic Press.
Sihombing, F., and Torbol, M. (2018). Parallel fault tree analysis for accurate reliability of complex systems. Structural Safety, Vol. 72, pp. 41-53.
Shalev, D. M., and Tiran, J. (2007). Condition-based fault tree analysis (CBFTA): a new method for improved fault tree analysis (FTA), reliability and safety calculations. Reliability Engineering & System Safety, Vol. 92(9), pp. 1231–1241.
Verma, A. K., Srividya, A., and Gaonkar, R. P. (2004). Fuzzy dynamic reliability evaluation of a deteriorating system      under imperfect repair. International Journal of Reliability, Quality and Safety Engineering, Vol. 11(04), pp. 387-398.
Van DerHorn, E., and Mahadevan, S. (2018). Bayesian model updating with summarized statistical and reliability data. Reliability Engineering & System Safety, Vol. 172, pp. 12-24.
Zhou, Q., Wong, Y. D., Loh, H. S., and Yuen, K. F. (2018). A fuzzy and Bayesian network CREAM model for human reliability analysis–The case of tanker shipping. Safety science, Vol.105, pp. 149-157.