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Intelligent risk prediction of storage tank leakage using an Ishikawa diagram with probability and impact analysis

Intelligent risk prediction of storage tank leakage using an Ishikawa diagram with probability and impact analysis
Intelligent risk prediction of storage tank leakage using an Ishikawa diagram with probability and impact analysis
Intelligent probability and impact analysis are used with an Ishikawa diagram. Causes of tank leakage events are identified. Causes were ranked and weights assigned to show their relative importance in the diagram. A Risk Score for each category of causes is identified using probability and impact analysis. The application is explored to predict the risk of leakage in a storage tank. That risk can be mixed with real time data to create an intelligent system. Various methods can be used to predict future system states centred upon an analysis of trends within historic or past data. A simple human computer interface is presented to display the results by overlaying ‘Fail’ or ‘Warning’ states on a schematic of a storage tank. Important information can be flagged alongside conditions. As an example, a surface graph, representing the storage tank condition over a ten-week period is displayed. A continuing deterioration in the score connected with “lack of operating procedures” is presented.
Ishikawa, Petroleum, Risk analysis, Storage tank
2194-5357
604-616
Springer
Ikwan, Favour
504e862a-ecff-41ce-85ba-38d95e34aad1
Sanders, David
54f2f76a-f55a-42d7-ac56-2e9fd8d92de4
Haddad, Malik
cdc55972-df6f-492d-8ed0-b022e19b912f
Hassan, Mohamed
ce323212-f178-4d72-85cf-23cd30605cd8
Omoarebun, Peter
d2bac592-82c7-450c-830c-49a7334fda1e
Thabet, Mohamad
d6026667-fef0-44a5-99d1-1520a35dfbd3
Tewkesbury, Giles
f569295c-fb95-4288-a6bc-7d9e5af15b8d
Vuksanovic, Branislav
a5fdf889-2472-4662-ba73-f2002df5c390
Arai, Kohei
Kapoor, Supriya
Bhatia, Rahul
Ikwan, Favour
504e862a-ecff-41ce-85ba-38d95e34aad1
Sanders, David
54f2f76a-f55a-42d7-ac56-2e9fd8d92de4
Haddad, Malik
cdc55972-df6f-492d-8ed0-b022e19b912f
Hassan, Mohamed
ce323212-f178-4d72-85cf-23cd30605cd8
Omoarebun, Peter
d2bac592-82c7-450c-830c-49a7334fda1e
Thabet, Mohamad
d6026667-fef0-44a5-99d1-1520a35dfbd3
Tewkesbury, Giles
f569295c-fb95-4288-a6bc-7d9e5af15b8d
Vuksanovic, Branislav
a5fdf889-2472-4662-ba73-f2002df5c390
Arai, Kohei
Kapoor, Supriya
Bhatia, Rahul

Ikwan, Favour, Sanders, David, Haddad, Malik, Hassan, Mohamed, Omoarebun, Peter, Thabet, Mohamad, Tewkesbury, Giles and Vuksanovic, Branislav (2021) Intelligent risk prediction of storage tank leakage using an Ishikawa diagram with probability and impact analysis. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (eds.) In Intelligent Systems and Applications - Proceedings of the 2020 Intelligent Systems Conference IntelliSys Volume 3. vol. 1252 AISC, Springer. pp. 604-616 . (doi:10.1007/978-3-030-55190-2_45).

Record type: Conference or Workshop Item (Paper)

Abstract

Intelligent probability and impact analysis are used with an Ishikawa diagram. Causes of tank leakage events are identified. Causes were ranked and weights assigned to show their relative importance in the diagram. A Risk Score for each category of causes is identified using probability and impact analysis. The application is explored to predict the risk of leakage in a storage tank. That risk can be mixed with real time data to create an intelligent system. Various methods can be used to predict future system states centred upon an analysis of trends within historic or past data. A simple human computer interface is presented to display the results by overlaying ‘Fail’ or ‘Warning’ states on a schematic of a storage tank. Important information can be flagged alongside conditions. As an example, a surface graph, representing the storage tank condition over a ten-week period is displayed. A continuing deterioration in the score connected with “lack of operating procedures” is presented.

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More information

e-pub ahead of print date: 25 August 2020
Published date: 2021
Keywords: Ishikawa, Petroleum, Risk analysis, Storage tank

Identifiers

Local EPrints ID: 444157
URI: http://eprints.soton.ac.uk/id/eprint/444157
ISSN: 2194-5357
PURE UUID: e946b9f6-65ad-476c-8ac9-7516523ae20c
ORCID for Mohamed Hassan: ORCID iD orcid.org/0000-0003-3729-4543

Catalogue record

Date deposited: 29 Sep 2020 17:39
Last modified: 18 Feb 2021 17:41

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Contributors

Author: Favour Ikwan
Author: David Sanders
Author: Malik Haddad
Author: Mohamed Hassan ORCID iD
Author: Peter Omoarebun
Author: Mohamad Thabet
Author: Giles Tewkesbury
Author: Branislav Vuksanovic
Editor: Kohei Arai
Editor: Supriya Kapoor
Editor: Rahul Bhatia

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