Abstract
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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Skalny, P., Krajc, B. (2013). Discrete-Time Markov Chains in Reliability Analysis-Case Study. In: Herrero, Á., et al. International Joint Conference CISIS’12-ICEUTE´12-SOCO´12 Special Sessions. Advances in Intelligent Systems and Computing, vol 189. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33018-6_43
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DOI: https://doi.org/10.1007/978-3-642-33018-6_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33017-9
Online ISBN: 978-3-642-33018-6
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