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A Novel Risk Analysis Approach for Occupational Safety Using Bayesian Network and Interval Type-2 Fuzzy Sets: the Case of Underground Mining

dc.contributor.author Yaşlı, Fatma
dc.contributor.author Yaşlı, Fatma
dc.contributor.author Bolat, Bersam
dc.contributor.other 01.01. Units Affiliated to the Rectorate
dc.contributor.other 01. Izmir Institute of Technology
dc.date.accessioned 2022-08-24T08:40:38Z
dc.date.available 2022-08-24T08:40:38Z
dc.date.issued 2022
dc.description.abstract Occupational safety problems are no longer acceptable for any industrial environment. Lack of comprehensive and reliable evaluations for occupational safety causes many undesired events and harm to employees during the industrial process. In this study, it is aimed to develop an applicable risk analysis methodology for evaluating the undesired occupational events that occurred in the multi-process system where no historical accident records. The difficulty in obtaining and analyzing the data required for the determination of the occupational safety risks especially in the manually executed processes has been overcome with the Bayesian Network and interval type-2 fuzzy sets by using the expert judgments. While BN enables to development of a comprehensive reasoning approach about the occurrence of the events, interval type-2 fuzzy sets better represent the ambiguity in the judgments by covering the uncertainty in a wider mathematical range with less computational effort according to other fuzzy sets. During multi-processes in industrial activity, various occupational undesired events may occur, including rare events with very serious consequences or frequent events with very low severity consequences. To able to consider all kinds of events occurring in an industrial environment from a holistic risk perspective, a novel fuzzy scale for specifying the probability and consequence of the events are proposed by the interval type-2 fuzzy numbers. Therefore, all undesired events regardless the probability and consequence which may occur during the multi-processes in a system and the main root causes of these events can be observed within the proposed methodology. A case study is used to emphasize the effect of the proposed methodology for risk analysis of occupational safety in underground mining The results have indicated that occupational safety education is the most contributing factor to occurring the undesired occupational events in underground mining We believe that this study could help evaluate the safety risk of the multi-process systems comprehensively and holistically and proposing strategic planning for mitigating the occupational safety risks. en_US
dc.description.endpage 282 en_US
dc.description.issue 1 en_US
dc.description.startpage 265 en_US
dc.description.volume 42 en_US
dc.identifier.doi 10.3233/JIFS-219191
dc.identifier.issn 1064-1246
dc.identifier.scopus 2-s2.0-85122780382
dc.identifier.uri http://dx.doi.org/10.3233/JIFS-219191
dc.identifier.uri https://hdl.handle.net/11147/12404
dc.language.iso en en_US
dc.publisher IOS Press BV en_US
dc.relation.ispartof Journal of Intelligent and Fuzzy Systems en_US
dc.relation.issn 1064-1246 en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Bayesian Network en_US
dc.subject Fuzzy sets en_US
dc.subject Occupational safety en_US
dc.title A Novel Risk Analysis Approach for Occupational Safety Using Bayesian Network and Interval Type-2 Fuzzy Sets: the Case of Underground Mining en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Bolat, Bersam
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.contributor.affiliation Anadolu Üniversitesi en_US
gdc.contributor.affiliation 01. Izmir Institute of Technology en_US
gdc.description.department İzmir Institute of Technology. Rectorate en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q3
gdc.description.wosquality Q4
gdc.identifier.openalex W3178531131
gdc.identifier.wos WOS:000741363900022
gdc.openalex.fwci 0.288
gdc.openalex.normalizedpercentile 0.66
gdc.opencitations.count 4
gdc.scopus.citedcount 5
gdc.wos.citedcount 5
relation.isAuthorOfPublication 54ab104f-cb74-40fa-82bd-4870ca39d8c2
relation.isAuthorOfPublication.latestForDiscovery 54ab104f-cb74-40fa-82bd-4870ca39d8c2
relation.isOrgUnitOfPublication 9711dc3e-de1f-44ab-8c8a-00d8a2db8ba5
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relation.isOrgUnitOfPublication.latestForDiscovery 9711dc3e-de1f-44ab-8c8a-00d8a2db8ba5

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