Bayesian Network-based Proactive Maintenance

  • Alexandre Muller
  • Marie-Christine Suhner
  • Benoît Iung


Today, the degradation mastery of critical components is one of the efficient means to minimise the non expected stops of production system and reduce its costs. Consequently, a prognosis process-based proactive maintenance system is proposed and formalized in this paper. This process allows to follow the system degradation and to implement adequate preventive actions for anticipating failures. Its development combines both probabilistic and event approaches for degradation mechanism modelling and dynamical monitoring.


Dynamic Bayesian Network Output Flow Input Flow Prognostic Method Condition Base Maintenance 
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 2004

Authors and Affiliations

  • Alexandre Muller
    • 1
  • Marie-Christine Suhner
    • 1
  • Benoît Iung
    • 1
  1. 1.Centre de Recherche en Automatique de Nancy (CRAN)Vandoeuvre-les-NancyFrance

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