Discrete-Time Markov Chains in Reliability Analysis-Case Study

  • Pavel Skalny
  • Bohumil Krajc
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 189)


This paper presents reliability analysis drawn up for an industrial firm. The main goal of this paper is to estimate the probability of firms failure to satisfy an order to its industrial partners. The second aim is to quantify expected value of amount of manufactured products for specific time period. Discrete Markov chains- well-known method of stochastic modelling describes the issue. The method is suitable for many systems occurring in practice where we can easily distinguish various amount of states. The disadvantage of Markov chains is that the amount of computations usually increases rapidly with the amount of states. The Monte Carlo method was implemented to deal with the problem. Chebyshev’s inequality was applied to estimate sufficient number of simulations.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Applied MathematicsVSB-Technical University of OstravaOstravaCzech Republic

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