A Markov model of a complex technical system operating in basic and emergency modes

• Autorzy: Malinowski J.
• Języki publikacji: EN

Abstrakty

EN

A complex technical system built of independent repairable components with constant failure and repair rates is examined. The system can operate in either basic or emergency mode, and its behavior is modeled by a three-state Markov process. It is demonstrated how to obtain closed formulas for the state probabilities of this process and the so-called importances of individual components to the inter-state transitions. Such an importance is defined as the probability that a component’s failure/repair causes a transition between two given states of the modeling process. The obtained formulas allow to compute a number of reliability parameters characterizing the dynamics of the system’s operation. The obtained results are illustrated by their application to an exemplary reliability block diagram that can be a model of a power supply network, a gas or oil pipeline system, etc.

Słowa kluczowe

EN

multi-state system; Markov process; failure rate; repair rate; component importance; transition intensity

• Wydawca: Polskie Towarzystwo Bezpieczeństwa i Niezawodności
• Czasopismo: Journal of Polish Safety and Reliability Association
• Rocznik: 2015
• Tom: Vol. 6, No. 2
• Strony: 89--96
• Opis fizyczny: Bibliogr. 6 poz., rys.

Twórcy

autor

Malinowski J.

• Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland

Bibliografia

• [1] Barlow, R. E. & Proschan, F. (1975). Statistical Theory of Reliability and Life Testing. Probability Models. Holt Rinehart and Winston, Inc., New York.
• [2] Chowdhury, A. & Koval, D. (2009). Power Distribution System Reliability: Practical Methods and Applications. John Wiley & Sons.
• [3] Karpinski, J. & Korczak, E. (1990). Methods of reliability assessment for two-state technical systems. (in Polish) Omnitech Press, Warszawa.
• [4] Korczak, E. (2007). New formula for the failure/repair frequency of multi-state monotone systems and its applications. Control and Cybernetics 36, 219-239.
• [5] Kuo, W. & Zhu, X. (2012). Importance Measures in Reliability, Risk, and Optimization. John Wiley & Sons.
• [6] Lisnianski, A. et al. (2010). Multi-State System Reliability Analysis and Optimization for Engineers and Industrial Managers. Springer.