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Complex Technical System Components Reliability and Safety Identification

  • Krzysztof Kołowrocki
  • Joanna Soszyńska-Budny
Chapter
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Abstract

The procedures and formulae estimating the unknown parameters of complex technical system components’ reliability and safety models on the basis of statistical data coming from the components reliability and safety states changing processes are presented. The maximum likelihood method is applied to estimate the unknown intensities of departures from the reliability and safety state subsets of the multistate system components having different exponential reliability functions at various system operation states. This method is applied to the statistical data collected in different kinds of empirical experiments, including small number of realizations and non-completed investigations. There is presented the goodness-of-fit test applied to verify the hypotheses concerned with the exponential forms of the multistate reliability functions of the particular components of the complex technical systems at variable operating conditions. In the case of lack of data coming from the components’ reliability and safety states changing processes, the simplified method of estimating the unknown intensities of departures from the reliability and safety state subsets based on expert opinion is proposed. Applications of the proposed statistical methods of unknown parameters’ identification of complex technical system components’ reliability and safety models to determine the reliability parameters of the exemplary system and the port oil transportation system components and the safety parameters of the maritime ferry technical system components are presented as well.

Keywords

System Component Operation State Reliability State Safety State Reliability Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Krzysztof Kołowrocki
    • 1
  • Joanna Soszyńska-Budny
    • 1
  1. 1.Maritime UniversityGdyniaPoland

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