Details
| Original language | English |
|---|---|
| Title of host publication | Safety and Reliability |
| Subtitle of host publication | Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018 |
| Editors | Stein Haugen, Anne Barros, Jan Erik Vinnem, Coen van Gulijk, Trond Kongsvik |
| Chapter | 42 |
| Pages | 329-338 |
| Number of pages | 10 |
| ISBN (electronic) | 9781351174664 |
| Publication status | Published - 2018 |
| Event | 28th International European Safety and Reliability Conference, ESREL 2018 - Trondheim, Norway Duration: 17 Jun 2018 → 21 Jun 2018 |
Abstract
Airplanes, ships, nuclear power plants and chemical production plants (including oil & gas facilities) are examples of industries that depend upon the interaction between operators and machines. Consequently, to assess the risks of those systems, not only the reliability of the technological components has to be accounted for, but also the ‘human model’. For this reason, engineers have been working together with psychologists and sociologists to understand cognitive functions and how the organisational context influences individual actions. Human Reliability Analysis (HRA) identifies and analyses the causes, consequences and contributions of human performance (including failures) in complex sociotechnical systems. Generally, HRA research is concentrated in modelling workers’ performance in the “sharp-end”, assessing the ones directly involved in handling the system, especially operators. However, in theory, a reliability analysis can be applied to any kind of human action, including those from designers and managers. This research will evaluate a way of conducting HRA in the design process, as previous research has demonstrated that design failure is the predominant contributor to human errors (Moura et al., 2016). Bayesian Network (BN) – a systematic way of learning from experience and incorporating new evidence (deterministic or probabilistic) – is proposed to model the complex relationships within cognitive functions, organisational and technological factors. Conditional probability tables have been obtained from a dataset of major accidents from different industry sectors (Moura et al. 2017), using a classification scheme developed by Hollnagel (1998) for an HRA method called CREAM – Cognitive Reliability and Error Analysis Method. The model allows to infer which factors most influence human performance in different scenarios. Also, we will discuss if the model can be applied to any human actions through the project life cycle— since the design phase to the operational phase, including their management.
ASJC Scopus subject areas
- Engineering(all)
- Safety, Risk, Reliability and Quality
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Safety and Reliability: Safe Societies in a Changing World - Proceedings of the 28th International European Safety and Reliability Conference, ESREL 2018. ed. / Stein Haugen; Anne Barros; Jan Erik Vinnem; Coen van Gulijk; Trond Kongsvik. 2018. p. 329-338.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Human reliability analysis
T2 - 28th International European Safety and Reliability Conference, ESREL 2018
AU - Morais, C.
AU - Moura, R.
AU - Beer, M.
AU - Patelli, E.
N1 - Publisher Copyright: © 2018 Taylor & Francis Group, London. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2018
Y1 - 2018
N2 - Airplanes, ships, nuclear power plants and chemical production plants (including oil & gas facilities) are examples of industries that depend upon the interaction between operators and machines. Consequently, to assess the risks of those systems, not only the reliability of the technological components has to be accounted for, but also the ‘human model’. For this reason, engineers have been working together with psychologists and sociologists to understand cognitive functions and how the organisational context influences individual actions. Human Reliability Analysis (HRA) identifies and analyses the causes, consequences and contributions of human performance (including failures) in complex sociotechnical systems. Generally, HRA research is concentrated in modelling workers’ performance in the “sharp-end”, assessing the ones directly involved in handling the system, especially operators. However, in theory, a reliability analysis can be applied to any kind of human action, including those from designers and managers. This research will evaluate a way of conducting HRA in the design process, as previous research has demonstrated that design failure is the predominant contributor to human errors (Moura et al., 2016). Bayesian Network (BN) – a systematic way of learning from experience and incorporating new evidence (deterministic or probabilistic) – is proposed to model the complex relationships within cognitive functions, organisational and technological factors. Conditional probability tables have been obtained from a dataset of major accidents from different industry sectors (Moura et al. 2017), using a classification scheme developed by Hollnagel (1998) for an HRA method called CREAM – Cognitive Reliability and Error Analysis Method. The model allows to infer which factors most influence human performance in different scenarios. Also, we will discuss if the model can be applied to any human actions through the project life cycle— since the design phase to the operational phase, including their management.
AB - Airplanes, ships, nuclear power plants and chemical production plants (including oil & gas facilities) are examples of industries that depend upon the interaction between operators and machines. Consequently, to assess the risks of those systems, not only the reliability of the technological components has to be accounted for, but also the ‘human model’. For this reason, engineers have been working together with psychologists and sociologists to understand cognitive functions and how the organisational context influences individual actions. Human Reliability Analysis (HRA) identifies and analyses the causes, consequences and contributions of human performance (including failures) in complex sociotechnical systems. Generally, HRA research is concentrated in modelling workers’ performance in the “sharp-end”, assessing the ones directly involved in handling the system, especially operators. However, in theory, a reliability analysis can be applied to any kind of human action, including those from designers and managers. This research will evaluate a way of conducting HRA in the design process, as previous research has demonstrated that design failure is the predominant contributor to human errors (Moura et al., 2016). Bayesian Network (BN) – a systematic way of learning from experience and incorporating new evidence (deterministic or probabilistic) – is proposed to model the complex relationships within cognitive functions, organisational and technological factors. Conditional probability tables have been obtained from a dataset of major accidents from different industry sectors (Moura et al. 2017), using a classification scheme developed by Hollnagel (1998) for an HRA method called CREAM – Cognitive Reliability and Error Analysis Method. The model allows to infer which factors most influence human performance in different scenarios. Also, we will discuss if the model can be applied to any human actions through the project life cycle— since the design phase to the operational phase, including their management.
UR - http://www.scopus.com/inward/record.url?scp=85058069974&partnerID=8YFLogxK
U2 - 10.1201/9781351174664-42
DO - 10.1201/9781351174664-42
M3 - Conference contribution
AN - SCOPUS:85058069974
SN - 9780815386827
SP - 329
EP - 338
BT - Safety and Reliability
A2 - Haugen, Stein
A2 - Barros, Anne
A2 - Vinnem, Jan Erik
A2 - van Gulijk, Coen
A2 - Kongsvik, Trond
Y2 - 17 June 2018 through 21 June 2018
ER -