Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/10215
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dc.contributor.authorSupciller, A.A.-
dc.contributor.authorAbali, N.-
dc.date.accessioned2019-08-16T13:13:42Z-
dc.date.available2019-08-16T13:13:42Z-
dc.date.issued2015-
dc.identifier.issn0748-8017-
dc.identifier.urihttps://hdl.handle.net/11499/10215-
dc.identifier.urihttps://doi.org/10.1002/qre.1908-
dc.description.abstractThe increase in industrialization necessitates risk analysis with a legal obligation all over the world. Therefore, risk analysis is very important for the safety culture of a company. Many qualitative and quantitative risk analysis methods contain subjective elements and uncertainty. In this study, risk analysis with the fuzzy proportional risk assessment technique (PRAT) is proposed for the first time to overcome the drawbacks of the conventional PRAT method. Three parameters, probability, frequency, and severity, are fuzzified by using appropriate membership functions. If-then rules and fuzzy logic operations are defined, and then, an inference is made to determine the riskiness. After defuzzification, the risk score is determined for each defined event. The results of conventional PRAT and fuzzy PRAT are compared in a case study carried out in a textile company that manufactures towels and bathrobes. Risk analysis based on fuzzy operations provides more precise measurements than the conventional risk analysis method employed by PRAT. Fuzzy PRAT provides more detailed risk analysis results, allows a direct interpretation of the risks with clusters of clear intervals, and produces a more realistic dataset than conventional PRAT. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.en_US
dc.language.isoenen_US
dc.publisherJohn Wiley and Sons Ltden_US
dc.relation.ispartofQuality and Reliability Engineering Internationalen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectfuzzyen_US
dc.subjectproportional risk assessment techniqueen_US
dc.subjectrisk analysisen_US
dc.subjectsafetyen_US
dc.subjecttextileen_US
dc.subjectAccident preventionen_US
dc.subjectFuzzy logicen_US
dc.subjectHealth risksen_US
dc.subjectIndustrial hygieneen_US
dc.subjectMembership functionsen_US
dc.subjectRisk assessmenten_US
dc.subjectRisksen_US
dc.subjectSafety engineeringen_US
dc.subjectTextilesen_US
dc.subjectUncertainty analysisen_US
dc.subjectAssessment techniqueen_US
dc.subjectLegal obligationsen_US
dc.subjectOccupational health and safetyen_US
dc.subjectPrecise measurementsen_US
dc.subjectQuantitative risk analysisen_US
dc.subjectRisk analysis methodsen_US
dc.subjectThree parametersen_US
dc.subjectRisk analysisen_US
dc.titleOccupational Health and Safety Within the Scope of Risk Analysis with Fuzzy Proportional Risk Assessment Technique (Fuzzy Prat)en_US
dc.typeArticleen_US
dc.identifier.volume31en_US
dc.identifier.issue7en_US
dc.identifier.startpage1137-
dc.identifier.startpage1137en_US
dc.identifier.endpage1150en_US
dc.identifier.doi10.1002/qre.1908-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopus2-s2.0-84945314248en_US
dc.identifier.wosWOS:000363876000005en_US
dc.identifier.scopusqualityQ1-
dc.ownerPamukkale University-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeArticle-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
crisitem.author.dept10.09. Industrial Engineering-
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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