Assessment of the optimal preventive maintenance period using stochastic hybrid modelling

Also the maintenance world is heading towards the era of artificial intelligence applied to the evaluation of the residual life of devices and predictive maintenance. On the other hand, when the operating conditions can change significantly and randomly, influencing the performance of the system sub...

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Bibliographic Details
Published inProcedia computer science Vol. 200; pp. 1664 - 1673
Main Authors D’Urso, D., Sinatra, A., Compagno, L., Chiacchio, F.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2022
Subjects
Bearings
Monte Carlo Simulation
Preventive Maintenance
Stochastic Hybrid Automation
Preventive Maintenance
Bearings
Monte Carlo Simulation
Stochastic Hybrid Automation
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ISSN1877-0509
1877-0509
DOI10.1016/j.procs.2022.01.367

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Summary:Also the maintenance world is heading towards the era of artificial intelligence applied to the evaluation of the residual life of devices and predictive maintenance. On the other hand, when the operating conditions can change significantly and randomly, influencing the performance of the system subject to aging phenomena, then the use of a stochastic hybrid approach for the reliability modeling of the system can lead to a closer representation of the reality. This latter approach is applied to the evaluation of the costs associated with the preventive maintenance of the bearings of a centrifugal pump used in petroleum processes. The evaluation is obtained by means of the Monte Carlo simulation methodology.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2022.01.367