How to Monitor Asset or Process Health with Fingerprints for Early Detection using CSense 2024
In this video we'll see how a process engineer can monitor asset or process health using multivariate fingerprints using Proficy CSense for early detection of problems.
You will see how to visually select data representing optimal conditions and feed this data into the CSense Architect, where the model can be created, then published to an external system such as a SCADA or a DCS, to improve failure detection and avoid issues.
Proficy CSense from GE Vernova uses AI and machine learning to enable process engineers to combine data across industrial data sources and rapidly identify problems, discover root causes, predict future performance, and automate actions to continuously improve quality, utilization, productivity, and delivery of operations.
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© 2024 GE Vernova and/or its affiliates. All rights reserved. GE and the GE Monogram are trademarks of General Electric Company used under trademark license. The information contained in this video is believed to be accurate and reliable. However, GE Vernova assumes no responsibilities for any errors, omissions or inaccuracies. Information contained in the video is subject to change without notice.
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