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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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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]. |
format | Online Article Text |
id | pubmed-6811953 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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