Abstract
Markov models are well established technique used widely for modeling equipment deterioration. This work presents an approach where Markov models represent equipment ageing and also incorporate various maintenance activities. Having available some basic model it is possible to adjust its parameters so that it represents some hypothetical new maintenance policy and then to examine impact that this new policy has on various reliability characteristics of the system. The paper deals with a method of model adjustment and specifically investigates its one particular problem: avoiding probability saturation in a model which is tuned towards increased repair frequencies. The text describes the adjustment method in a general case, identifies specific risk of probability saturation that may take place during the iterative procedure and proposes a new extension to the method that overcomes this problem with minimal intervention in the internal structure of the model, in a specific class of cases.
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Sugier, J. (2011). Avoiding Probability Saturation during Adjustment of Markov Models of Ageing Equipment. In: Zamojski, W., Kacprzyk, J., Mazurkiewicz, J., Sugier, J., Walkowiak, T. (eds) Dependable Computer Systems. Advances in Intelligent and Soft Computing, vol 97. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21393-9_16
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DOI: https://doi.org/10.1007/978-3-642-21393-9_16
Publisher Name: Springer, Berlin, Heidelberg
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