Fine–kinney-based occupational risk assessment using intuitionistic fuzzy todim

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Özet

This chapter applies a novel occupational risk assessment approach which merges TODIM with the Fine–Kinney method under the intuitionistic fuzzy set concept. Risk parameters of Fine–Kinney and OHS experts are weighted by an intuitionistic fuzzy weighted averaging (IFWA) aggregation operator. Hence, hazards are quantitatively evaluated and prioritized using the proposed approach. To illustrate the novel risk assessment approach, processes of the gun and rifle assembly line of a factory are handled. A comprehensive risk assessment is carried out to improve operational safety and reliability in the industry. We adapt intuitionistic fuzzy sets in the existing study since they reflect uncertainty with the aid of their membership and nonmembership functions in decision-making better than classical fuzzy extensions. An additional sensitivity analysis by changing the attenuation parameter of TODIM is performed to test the validity of the approach. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.

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https://rdlopen.rawdatalibrary.net/r/munzur/2656Resmi atıflarda kullanılan kalıcı adres
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https://doi.org/10.1007/978-3-030-52148-6_5Yayıncı resmi DOI adresi
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dc.contributor.authorGul, Muhammet
dc.contributor.authorMete, Suleyman
dc.contributor.authorSerin, Faruk
dc.contributor.authorCelik, Erkan
dc.date.accessioned2026-10-28T14:55:39.353568453Z
dc.date.available2026-10-28T14:55:39.353568453Z
dc.date.issued2021
dc.description.abstractThis chapter applies a novel occupational risk assessment approach which merges TODIM with the Fine–Kinney method under the intuitionistic fuzzy set concept. Risk parameters of Fine–Kinney and OHS experts are weighted by an intuitionistic fuzzy weighted averaging (IFWA) aggregation operator. Hence, hazards are quantitatively evaluated and prioritized using the proposed approach. To illustrate the novel risk assessment approach, processes of the gun and rifle assembly line of a factory are handled. A comprehensive risk assessment is carried out to improve operational safety and reliability in the industry. We adapt intuitionistic fuzzy sets in the existing study since they reflect uncertainty with the aid of their membership and nonmembership functions in decision-making better than classical fuzzy extensions. An additional sensitivity analysis by changing the attenuation parameter of TODIM is performed to test the validity of the approach. Finally, the Python codes in the implementation of the proposed approach are given for scholars and practitioners for usage in further studies.
dc.identifier.doi10.1007/978-3-030-52148-6_5
dc.identifier.endpage89
dc.identifier.issn1434-9922
dc.identifier.scopus2-s2.0-85091897304
dc.identifier.startpage69
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/2656
dc.identifier.volume398
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofStudies in Fuzziness and Soft Computing
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleFine–kinney-based occupational risk assessment using intuitionistic fuzzy todim
dc.typeBook Chapter
rdl.citation.openalex9
rdl.citation.scopus5
rdl.oa.statusclosed
rdl.source.indexSCOPUS