Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/10780
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dc.contributor.authorDjapan, Marko-
dc.contributor.authorMacuzic, Ivan-
dc.contributor.authorTadić, Danijela-
dc.contributor.authorBaldissone G.-
dc.date.accessioned2021-04-20T16:39:06Z-
dc.date.available2021-04-20T16:39:06Z-
dc.date.issued2019-
dc.identifier.issn0925-7535-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/10780-
dc.description.abstract© 2018 Elsevier Ltd The article deals with an innovative methodology for risk assessment concerning human, organizational and technical/technological (HOT) factors, based on fuzzy set theory. The aim of this paper is to propose user-friendly prognostic risk assessment tool (PgRA) by obtaining reliable results and supporting further decisions of the safety managers. The HOT factors are introduced with associated sub-factors. The user-friendly interface developed in Matlab environment provides multiple opportunities for further improvement. The settings presented in this article are strictly applied for, but not limited to manufacturing sector. Flexibility of the PgRA tool allows adjustments and customize model regarding the group of the companies. With introduction of fuzzy set theory in the risk assessment process, level of subjectivity is reduced to the minimum. Practical applications: Possibilities of the practical application are modeled to assist in decrease of identified risks during daily work. This is a useful visual management tool, helpful to all safety managers in planning workplace improvements. The safety managers are in position to predict risk level before the real measures are taken. They are able to show the possible realistic results and risk trend behaviour to their supervisor/director, without spending any financial resources.-
dc.rightsrestrictedAccess-
dc.sourceSafety Science-
dc.titleAn innovative prognostic risk assessment tool for manufacturing sector based on the management of the human, organizational and technical/technological factors-
dc.typearticle-
dc.identifier.doi10.1016/j.ssci.2018.02.032-
dc.identifier.scopus2-s2.0-85042934458-
Appears in Collections:Faculty of Engineering, Kragujevac

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