Probabilistic maintenance optimization with respect to inspection quality

DC FieldValueLanguage
dc.contributor.authorZou, Guang-
dc.contributor.authorBanisoleiman, Kian-
dc.contributor.authorGonzález, Arturo-
dc.date.accessioned2018-11-27T09:39:40Z-
dc.date.available2018-11-27T09:39:40Z-
dc.date.issued2018-09-12-
dc.identifier.urihttp://hdl.handle.net/10197/9571-
dc.descriptionThe 16th International Probabilistic Workshop (IPW2018), Vienna, Austria, 12-14 September 2018en_US
dc.description.abstractMaintenance scheduling and optimization against fatigue failures is of great interest for marine and offshore engineering in terms of safety assurance, integrity management and cost control. The main challenge is to make risk-informed and optimal maintenance decisions taking into account uncertainties associated with material properties, fatigue loads, modelling, inspection and maintenance methods. While optimization of inspection times has been the objectives of many studies, the influence and optimization of inspection qualities is not very clear. This paper has applied probabilistic fracture mechanics and reliability/risk methods to optimization of inspection quality as well as inspection time and revealed the effect of inspection quality on lifetime fatigue reliability. It is found that there is a reliability-based optimum inspection quality for maintenance scheduling, which is different from the cost-based optimum one. Better inspection quality than the optimum one can lead to excessive maintenance, which occurs when the effect of maintenance is not good, and the inspection quality applied is very good. Excessive maintenance can lead to increase of both expected failure costs and maintenance costs, and thus should be avoided.en_US
dc.description.sponsorshipEuropean Commission Horizon 2020en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of the 16th International Probabilistic Workshop (IPW 2018)en_US
dc.subjectProbabilistic maintenance optimizationen_US
dc.subjectInspection qualityen_US
dc.subjectFatigue modellingen_US
dc.titleProbabilistic maintenance optimization with respect to inspection qualityen_US
dc.typeConference Publicationen_US
dc.internal.authorcontactotherarturo.gonzalez@ucd.ieen_US
dc.internal.webversionshttp://probabilistic.boku.ac.at/-
dc.statusPeer revieweden_US
dc.check.date2018-05-07-
dc.neeo.contributorZou|Guang|aut|-
dc.neeo.contributorBanisoleiman|Kian|aut|-
dc.neeo.contributorGonzález|Arturo|aut|-
dc.description.adminCheckdate for published version - ACen_US
dc.date.updated2018-10-11T13:34:29Z-
dc.identifier.grantid642453: MSCA-ITN-2014-ETN-
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Critical Infrastructure Group Research Collection
Earth Institute Research Collection
Civil Engineering Research Collection
TRUSS-ITN Research Collection
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