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Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector
Human reliability analysis (HRA) is a major concern for organizations. While various tools, methods, and instruments have been developed by the scientific community to assess human error probability, few of them actually consider human factors impact in their analysis. The active role that workers h...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910755/ https://www.ncbi.nlm.nih.gov/pubmed/35270489 http://dx.doi.org/10.3390/ijerph19052797 |
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author | Guglielmi, Dina Paolucci, Alessio Cozzani, Valerio Mariani, Marco Giovanni Pietrantoni, Luca Fraboni, Federico |
author_facet | Guglielmi, Dina Paolucci, Alessio Cozzani, Valerio Mariani, Marco Giovanni Pietrantoni, Luca Fraboni, Federico |
author_sort | Guglielmi, Dina |
collection | PubMed |
description | Human reliability analysis (HRA) is a major concern for organizations. While various tools, methods, and instruments have been developed by the scientific community to assess human error probability, few of them actually consider human factors impact in their analysis. The active role that workers have in shaping their own performance should be taken into account in order to understand the causal factors that may lead to errors while performing a task and identifying which human factors may prevent errors from occurring. In line with this purpose, the aim of this study is to present a new methodology for the assessment of human reliability. The proposed model relies on well-known HRA methodologies (such as SPAR-H and HEART) and integrates them in a unified framework in which human factors assume the role of safety barriers against human error. A test case of the new method was carried out in a logistics hub of an energy company. Our results indicate that human factors play a significant role in preventing workers from making errors while performing tasks by reducing human error probability. The limits and implications of the study are discussed. |
format | Online Article Text |
id | pubmed-8910755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89107552022-03-11 Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector Guglielmi, Dina Paolucci, Alessio Cozzani, Valerio Mariani, Marco Giovanni Pietrantoni, Luca Fraboni, Federico Int J Environ Res Public Health Article Human reliability analysis (HRA) is a major concern for organizations. While various tools, methods, and instruments have been developed by the scientific community to assess human error probability, few of them actually consider human factors impact in their analysis. The active role that workers have in shaping their own performance should be taken into account in order to understand the causal factors that may lead to errors while performing a task and identifying which human factors may prevent errors from occurring. In line with this purpose, the aim of this study is to present a new methodology for the assessment of human reliability. The proposed model relies on well-known HRA methodologies (such as SPAR-H and HEART) and integrates them in a unified framework in which human factors assume the role of safety barriers against human error. A test case of the new method was carried out in a logistics hub of an energy company. Our results indicate that human factors play a significant role in preventing workers from making errors while performing tasks by reducing human error probability. The limits and implications of the study are discussed. MDPI 2022-02-27 /pmc/articles/PMC8910755/ /pubmed/35270489 http://dx.doi.org/10.3390/ijerph19052797 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Guglielmi, Dina Paolucci, Alessio Cozzani, Valerio Mariani, Marco Giovanni Pietrantoni, Luca Fraboni, Federico Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector |
title | Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector |
title_full | Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector |
title_fullStr | Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector |
title_full_unstemmed | Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector |
title_short | Integrating Human Barriers in Human Reliability Analysis: A New Model for the Energy Sector |
title_sort | integrating human barriers in human reliability analysis: a new model for the energy sector |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910755/ https://www.ncbi.nlm.nih.gov/pubmed/35270489 http://dx.doi.org/10.3390/ijerph19052797 |
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