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On reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach

BahooToroody Ahmad.; Kujala Pentti; Banda Osiris Valdez; Abaei Mohammad Mahdi; Montewka Jakub

dc.contributor.authorBahooToroody Ahmad.
dc.contributor.authorKujala Pentti
dc.contributor.authorBanda Osiris Valdez
dc.contributor.authorAbaei Mohammad Mahdi
dc.contributor.authorMontewka Jakub
dc.date.accessioned2022-10-28T13:24:54Z
dc.date.available2022-10-28T13:24:54Z
dc.identifier.urihttps://www.utupub.fi/handle/10024/165018
dc.description.abstract<p>Analyzing the reliability of autonomous ships has recently attracted attention mainly due to <a href="https://www.sciencedirect.com/topics/engineering/epistemic-uncertainty" title="Learn more about epistemic uncertainty from ScienceDirect's AI-generated Topic Pages">epistemic uncertainty</a> (lack of knowledge) integrated with automatic operations in the maritime sector. The advent of new random failures with unrecognized failure patterns in autonomous ship operations requires a comprehensive reliability assessment specifically aiming at estimating the time in which the ship can be trusted to be left unattended. While the reliability concept is touched upon well through the literature, the operational trustworthiness needs more elaboration to be established for system safety, especially within the maritime sector. Accordingly, in this paper, a <a href="https://www.sciencedirect.com/topics/engineering/probabilistic-approach" title="Learn more about probabilistic approach from ScienceDirect's AI-generated Topic Pages">probabilistic approach</a> has been established to estimate the trusted operational time of the ship machinery system through different autonomy degrees. The uncertainty associated with ship operation has been quantified using Markov Chain Monte-Carlo simulation from likelihood function in Bayesian inference. To verify the developed framework, a practical example of a machinery plant used in typical short sea merchant ships is taken into account. This study can be exploited by asset managers to estimate the time in which the ship can be left unattended. Keywords: reliability estimation, Bayesian inference, autonomous ship, uncertainty.<br></p>
dc.language.isoen
dc.publisherElsevier
dc.titleOn reliability assessment of ship machinery system in different autonomy degree; A Bayesian-based approach
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0029801822006473
dc.identifier.urnURN:NBN:fi-fe2022091258619
dc.relation.volume254
dc.contributor.organizationfi=maantiede|en=Geography |
dc.contributor.organization-code2606901
dc.converis.publication-id176240791
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/176240791
dc.identifier.jour-issn0029-8018
dc.okm.affiliatedauthorAbaei, Mahdi
dc.okm.discipline222 Muu tekniikkafi_FI
dc.okm.discipline222 Other engineering and technologiesen_GB
dc.okm.discipline214 Kone- ja valmistustekniikkafi_FI
dc.okm.discipline214 Mechanical engineeringen_GB
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeJournal article
dc.publisher.countryBritanniafi_FI
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.country-codeGB
dc.relation.articlenumber111252
dc.relation.doi10.1016/j.oceaneng.2022.111252
dc.relation.ispartofjournalOcean Engineering
dc.year.issued2022


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