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DOE OSTI · 2438465

Data Architecture and Analytics Requirements for Artificial Intelligence and Machine Learning Applications to Achieve Condition-Based Maintenance

Agarwal, Vivek·Joe, Jeffrey C.·Gribok, Andrei V.·Smith, James A.·Oxstrand, Johanna H.·Primer, Craig A.
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Abstract

This report identified some of the important requirements that needs to be taken into consideration as part of the data evolution for the CBM application of a CWS in a NPP. In the data evolution process, the information is converted into insight leading into actions using advancements in AI/ML technologies. A notion of RESET AI: design, development, deployment, and operation principals are introduced to lifecycle of AI technologies. Towards the end of the report, we discussed how this CBM can be realized in a SDE. As path forward, this report lays the foundation for developing a more detailed industry guidance supporting data evolution for other plant applications like operations and plant support. These would be developed as part of ongoing research in the fiscal year 2023.

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46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGYArtificial IntelligenceCondition-Based MaintenanceInformation AutomationSeamless Digital Environment

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Agarwal, Vivek, Joe, Jeffrey C., Gribok, Andrei V., Smith, James A., Oxstrand, Johanna H., Primer, Craig A.. 2022-11-01. Data Architecture and Analytics Requirements for Artificial Intelligence and Machine Learning Applications to Achieve Condition-Based Maintenance. https://doi.org/10.2172/2438465

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