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dc.contributor.authorUflaz, Esma
dc.contributor.authorSezer, Şükrü İlke
dc.contributor.authorAkyüz, Emre
dc.contributor.authorArslan, Özcan
dc.contributor.authorKurt, Rafet Emek
dc.date.accessioned2022-12-01T06:15:58Z
dc.date.available2022-12-01T06:15:58Z
dc.date.issued2022en_US
dc.identifier.citationUflaz, E., Sezer, S.I., Akyuz, E., Arslan, O., Kurt, R.E. (2022). A human reliability analysis for ship to ship LNG bunkering process under D-S evidence fusion HEART approach. Journal of Loss Prevention in the Process Industries, 80, art. no. 104887. https://doi.org/10.1016/j.jlp.2022.104887en_US
dc.identifier.issn0950-4230
dc.identifier.urihttps://doi.org/10.1016/j.jlp.2022.104887
dc.identifier.urihttps://hdl.handle.net/20.500.12508/2361
dc.description.abstractLNG (Liquid Natural Gas) ship to ship bunkering process is quite a new concept for the maritime industry since the usage of LNG has been increasing worldwide. The LNG bunkering process poses a high risk due to human errors, while a minor error may be catastrophic. The expectation of the ship's crew is to carry out operations without any errors. Therefore, human reliability analysis (HRA) is paramount to improving operational safety during the ship to ship LNG bunkering process. In this context, this paper performs a systematic HRA under the D–S (Dempster-Shafer) evidence fusion-based HEART (human error assessment and reduction technique) approach. While the HEART quantifies human error for the tasks being performed, the extended D-S evidence fusion deals with the limitation of APOA (assessing the proportion of effect) calculation since it significantly relies on evaluating a single rater. The finding shows that human reliability for the ship to ship LNG bunkering process is 5.98E-01 and reasonable, but not at the desired level. The paper's outcomes will contribute to the utmost for LNG ship operators, safety inspectors, and ship owners to establish a safe and efficient ship to ship LNG bunkering process and minimise human error-based accidents.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.isversionof10.1016/j.jlp.2022.104887en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectD-S evidence Fusion theoryen_US
dc.subjectHEARTen_US
dc.subjectHuman reliabilityen_US
dc.subjectLNG bunkering processen_US
dc.subject.classificationHuman Error
dc.subject.classificationNuclear Power Plants
dc.subject.classificationErgonomics
dc.subject.classificationEngineering
dc.subject.classificationElectrical Engineering, Electronics & Computer Science - Safety & Maintenance - Safety Climate
dc.subject.otherHuman error probabilities
dc.subject.otherLiquefied natural-gas
dc.subject.otherMaintenance procedures
dc.subject.otherRisk
dc.subject.otherOperations
dc.subject.otherFacilities
dc.subject.otherFramework
dc.subject.otherSystems
dc.subject.otherMarine
dc.subject.otherModel
dc.subject.otherErrors
dc.subject.otherHeart
dc.subject.otherLiquefied natural gas
dc.subject.otherReliability theory
dc.subject.otherSafety engineering
dc.subject.otherShips
dc.subject.otherAssessment technique
dc.subject.otherD-S evidence fusion theory
dc.subject.otherD-S evidences
dc.subject.otherError reduction
dc.subject.otherEvidence fusion
dc.subject.otherFusion theory
dc.subject.otherHuman error assessment
dc.subject.otherHuman error assessment and reduction technique
dc.subject.otherHuman reliability
dc.subject.otherLiquid natural gas
dc.subject.otherLiquid natural gas bunkering process
dc.subject.otherReduction techniques
dc.subject.otherReliability analysis
dc.titleA human reliability analysis for ship to ship LNG bunkering process under D-S evidence fusion HEART approachen_US
dc.typearticleen_US
dc.relation.journalJournal of Loss Prevention in the Process Industriesen_US
dc.contributor.departmentMühendislik ve Doğa Bilimleri Fakültesi -- Deniz Ulaştırma İşletme Mühendisliği Bölümüen_US
dc.identifier.volume80en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.contributor.isteauthorSezer, Şükrü İlke
dc.relation.indexWeb of Science - Scopusen_US
dc.relation.indexWeb of Science Core Collection - Science Citation Index Expanded


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