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Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy

Data were collected in an automotive production plant during a campaign of observations performed by safety experts. A period of one week of observations was done during which safety experts monitored the working activity of an assembly line. All accident-precursors identified were reported in a for...

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Autores principales: Baldissone, Gabriele, Demichela, Micaela, Comberti, Lorenzo, Murè, Salvina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811953/
https://www.ncbi.nlm.nih.gov/pubmed/31667244
http://dx.doi.org/10.1016/j.dib.2019.104479
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author Baldissone, Gabriele
Demichela, Micaela
Comberti, Lorenzo
Murè, Salvina
author_facet Baldissone, Gabriele
Demichela, Micaela
Comberti, Lorenzo
Murè, Salvina
author_sort Baldissone, Gabriele
collection PubMed
description Data were collected in an automotive production plant during a campaign of observations performed by safety experts. A period of one week of observations was done during which safety experts monitored the working activity of an assembly line. All accident-precursors identified were reported in a format and immediately analysed and classified according to HFACS. Each collected element was classified in 3 categories as: unsafe acts (related to human behaviour), unsafe condition (related to the working condition and working organisation) and near miss (a situation that involved workers without physical consequence for them). Then each element was classified according to the four levels of HFACS: individual factor (violation or error), environmental factor, supervision and organisational factor. This step was supported by short interview with workers and/or supervisors involved to better identify the characterising factors of the event. This survey allowed the identification and classification of 100 accident-precursors that could be used in the company where they have been collected and, more in general, in manufacturing companies, to identify behaviours and areas of improvement for health and safety based on more recurrent factors that characterised the observed events, according to the methodology described in Baldissone et al. [1].
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spelling pubmed-68119532019-10-30 Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy Baldissone, Gabriele Demichela, Micaela Comberti, Lorenzo Murè, Salvina Data Brief Engineering Data were collected in an automotive production plant during a campaign of observations performed by safety experts. A period of one week of observations was done during which safety experts monitored the working activity of an assembly line. All accident-precursors identified were reported in a format and immediately analysed and classified according to HFACS. Each collected element was classified in 3 categories as: unsafe acts (related to human behaviour), unsafe condition (related to the working condition and working organisation) and near miss (a situation that involved workers without physical consequence for them). Then each element was classified according to the four levels of HFACS: individual factor (violation or error), environmental factor, supervision and organisational factor. This step was supported by short interview with workers and/or supervisors involved to better identify the characterising factors of the event. This survey allowed the identification and classification of 100 accident-precursors that could be used in the company where they have been collected and, more in general, in manufacturing companies, to identify behaviours and areas of improvement for health and safety based on more recurrent factors that characterised the observed events, according to the methodology described in Baldissone et al. [1]. Elsevier 2019-09-04 /pmc/articles/PMC6811953/ /pubmed/31667244 http://dx.doi.org/10.1016/j.dib.2019.104479 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Engineering
Baldissone, Gabriele
Demichela, Micaela
Comberti, Lorenzo
Murè, Salvina
Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy
title Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy
title_full Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy
title_fullStr Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy
title_full_unstemmed Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy
title_short Occupational accident-precursors data collection and analysis according to Human Factors Analysis and Classification System (HFACS) taxonomy
title_sort occupational accident-precursors data collection and analysis according to human factors analysis and classification system (hfacs) taxonomy
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811953/
https://www.ncbi.nlm.nih.gov/pubmed/31667244
http://dx.doi.org/10.1016/j.dib.2019.104479
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