Process Alarm Modeling Using Graph Theory: Alarm Design Review and Rationalization

Parsa, K; Hassall, M; Naderpour, M

Process Alarm Modeling Using Graph Theory: Alarm Design Review and Rationalization

Parsa, K Hassall, M Naderpour, M

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Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Systems Journal, 2021, 15, (2), pp. 2257-2268
Issue Date:: 2021

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Field	Value	Language
dc.contributor.author	Parsa, K
dc.contributor.author	Hassall, M
dc.contributor.author	Naderpour, M https://orcid.org/0000-0002-3549-3875
dc.date.accessioned	2022-05-21T00:24:10Z
dc.date.available	2022-05-21T00:24:10Z
dc.date.issued	2021
dc.identifier.citation	IEEE Systems Journal, 2021, 15, (2), pp. 2257-2268
dc.identifier.issn	1932-8184
dc.identifier.issn	2373-7816
dc.identifier.uri	http://hdl.handle.net/10453/157592
dc.description.abstract	Investigations into process accidents have identified that flaws in alarm management systems are a major contributing factor to these accidents. Poor alarm system design can lead to alarm flooding, loss of situation awareness, and poor decision-making, causing unnecessary shutdowns, or further escalation of the abnormal situations. A review of research literature suggests that there appears to be limited methods available to help analysts evaluate alarm system design and to prioritize and rationalize alarms in a manner that promotes operators' situation awareness and correct decision-making. This article documents the first part of the research which aims to develop a means to rationalize defined alarms in operations through use of the causal modeling approach that is linked with the graph modeling technique that involves graph analytics to provide metrics to evaluate the alarm system performance. The article concludes by discussing the implications of the research findings and makes recommendations about further research required to fully develop an alarm system that use prioritization and rationalization to improve the operator's situation awareness and responses during abnormal operating situations.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation.ispartof	IEEE Systems Journal
dc.relation.isbasedon	10.1109/jsyst.2020.3019041
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Operations Research
dc.title	Process Alarm Modeling Using Graph Theory: Alarm Design Review and Rationalization
dc.type	Journal Article
utslib.citation.volume	15
utslib.for	0906 Electrical and Electronic Engineering
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/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-05-21T00:24:07Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	15
utslib.citation.issue	2

Abstract:

Investigations into process accidents have identified that flaws in alarm management systems are a major contributing factor to these accidents. Poor alarm system design can lead to alarm flooding, loss of situation awareness, and poor decision-making, causing unnecessary shutdowns, or further escalation of the abnormal situations. A review of research literature suggests that there appears to be limited methods available to help analysts evaluate alarm system design and to prioritize and rationalize alarms in a manner that promotes operators' situation awareness and correct decision-making. This article documents the first part of the research which aims to develop a means to rationalize defined alarms in operations through use of the causal modeling approach that is linked with the graph modeling technique that involves graph analytics to provide metrics to evaluate the alarm system performance. The article concludes by discussing the implications of the research findings and makes recommendations about further research required to fully develop an alarm system that use prioritization and rationalization to improve the operator's situation awareness and responses during abnormal operating situations.

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

http://hdl.handle.net/10453/157592