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Condition Monitoring, Root Cause Analysis and Decision Support on Urgency of Actions

  • We discuss the use of a hybrid system utilizing Object Oriented Bayesian networks and influence diagrams for probabilistic reasoning under uncertainties in industrial process operations. The Bayesian networks are used for condition monitoring and root cause analysis of process operation. The recommended decision sequence of corrective actions and observations is obtained following the "myopic" approach. The BN inference on most probable root cause is used in an influence diagram for taking decisions on urgency of corrective actions vs. delivery deadline. The build-in chain of causality from root cause to process faults can provide the user with explanation facility and a simulation tool of the effect of intended actions.

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Metadaten
Author:Galia WeidlORCiD, Anders L. Madsen, Erik Dahlquist
URL:https://www.researchgate.net/publication/228719447_Condition_Monitoring_Root_Cause_Analysis_and_Decision_Support_on_Urgency_of_Actions#fullTextFileContent
Parent Title (English):Book Series FAIA (Frontiers in Artificial Intelligence and Applications), Soft Computing Systems - Design, Management and Applications
Document Type:Article
Language:English
Year of Completion:2002
Release Date:2023/12/11
Tag:Bayesian Networks; OOBN
GND Keyword:Prozesssteuerung; Prozessanalyse
Volume:2002
Issue:87
First Page:221
Last Page:230
Urheberrecht:1
Institutes:Einrichtungen / Kompetenzzentrum Künstliche Intelligenz
research focus :Intelligent Systems / Artifical Intelligence and Data Science
Licence (German):Creative Commons - CC BY - Namensnennung 4.0 International
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