A situation risk awareness approach for process systems safety

Naderpour, M; Lu, J; Zhang, G

A situation risk awareness approach for process systems safety

Naderpour, M

Lu, J

Zhang, G

Permalink

Publication Type:: Journal Article
Citation:: Safety Science, 2014, 64 pp. 173 - 189
Issue Date:: 2014-04-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (1.19 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Naderpour, M https://orcid.org/0000-0002-3549-3875	en_US
dc.contributor.author	Lu, J https://orcid.org/0000-0003-0690-4732	en_US
dc.contributor.author	Zhang, G https://orcid.org/0000-0003-3960-0583	en_US
dc.date.available	2020-05-25T19:17:12Z
dc.date.issued	2014-04-01	en_US
dc.identifier.citation	Safety Science, 2014, 64 pp. 173 - 189	en_US
dc.identifier.issn	0925-7535	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32967
dc.description.abstract	Promoting situation awareness is an important design objective for a wide variety of domains, especially for process systems where the information flow is quite high and poor decisions may lead to serious consequences. In today's process systems, operators are often moved to a control room far away from the physical environment, and increasing amounts of information are passed to them via automated systems, they therefore need a greater level of support to control and maintain the facilities in safe conditions. This paper proposes a situation risk awareness approach for process systems safety where the effect of ever-increasing situational complexity on human decision-makers is a concern. To develop the approach, two important aspects - addressing hazards that arise from hardware failure and reducing human error through decision-making - have been considered. The proposed situation risk awareness approach includes two major elements: an evidence preparation component and a situation assessment component. The evidence preparation component provides the soft evidence, using a fuzzy partitioning method, that is used in the subsequent situation assessment component. The situation assessment component includes a situational network based on dynamic Bayesian networks to model the abnormal situations, and a fuzzy risk estimation method to generate the assessment result. A case from US Chemical Safety Board investigation reports has been used to illustrate the application of the proposed approach. © 2013 Elsevier Ltd.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP110103733
dc.relation.ispartof	Safety Science	en_US
dc.relation.isbasedon	10.1016/j.ssci.2013.12.005	en_US
dc.subject.classification	Human Factors	en_US
dc.title	A situation risk awareness approach for process systems safety	en_US
dc.type	Journal Article
utslib.citation.volume	64	en_US
utslib.for	080605 Decision Support and Group Support Systems	en_US
utslib.for	09 Engineering	en_US
utslib.for	11 Medical and Health Sciences	en_US
utslib.for	17 Psychology and Cognitive Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	64	en_US

Abstract:

Promoting situation awareness is an important design objective for a wide variety of domains, especially for process systems where the information flow is quite high and poor decisions may lead to serious consequences. In today's process systems, operators are often moved to a control room far away from the physical environment, and increasing amounts of information are passed to them via automated systems, they therefore need a greater level of support to control and maintain the facilities in safe conditions. This paper proposes a situation risk awareness approach for process systems safety where the effect of ever-increasing situational complexity on human decision-makers is a concern. To develop the approach, two important aspects - addressing hazards that arise from hardware failure and reducing human error through decision-making - have been considered. The proposed situation risk awareness approach includes two major elements: an evidence preparation component and a situation assessment component. The evidence preparation component provides the soft evidence, using a fuzzy partitioning method, that is used in the subsequent situation assessment component. The situation assessment component includes a situational network based on dynamic Bayesian networks to model the abnormal situations, and a fuzzy risk estimation method to generate the assessment result. A case from US Chemical Safety Board investigation reports has been used to illustrate the application of the proposed approach. © 2013 Elsevier Ltd.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/32967