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"Maintenance of solar tower power plants  STPP  is very important to ensure production continuity  However  random and non-optimal maintenance can increase the intervention cost  In this paper  a new procedure  based on the criticality analysis  was proposed to improve the maintenance of the STPP  This procedure is the combination of three methods  which are failure mode effects and criticality analysis  FMECA   Bayesian network and artificial intelligence  The FMECA is used to estimate the criticality index of the different elements of STPP  Moreover  corrections and improvements were introduced on the criticality index values based on the expert advice method  The modeling and the simulation of the FMECA estimations incorporating the expert advice method corrections were performed using the Bayesian network  The artificial neural network is used to predicate the criticality index of the STPP exploiting the database obtained from the Bayesian network simulations  The results showed a good agreement comparing predicted and actual criticality index values  In order to reduce the criticality index value of the critical elements of STPP  some maintenance recommendations were suggested "
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