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

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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.
Original languageEnglish
Title of host publicationIntelligent Systems and Applications
Subtitle of host publicationProceedings of the 2020 Intelligent Systems Conference (IntelliSys) Volume 3
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer
Pages604-616
ISBN (Electronic)978-3-030-55190-2
ISBN (Print)978-3-030-55189-6
DOIs
Publication statusPublished - 25 Aug 2020
EventIntelligent Systems Conference - London, United Kingdom
Duration: 3 Sep 20204 Sep 2020

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1252
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceIntelligent Systems Conference
Abbreviated titleIntelliSys 2020
CountryUnited Kingdom
CityLondon
Period3/09/204/09/20

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