How to Predict Product Quality using CSense 2024

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In this video we'll see how a process engineer can create a machine learning model to predict product quality that will help reduce laboratory testing – using Proficy CSense.

You will see how to feed the optimal data into the CSense Architect where the model can be created, then publish to an external system such as a SCADA or a DCS to improve quality and save cost.

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.

Video 1 of 5 -- from the Product and Process Quality series for CSense 2024. Next video in the series is:

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© 2024 GE Vernova and/or its affiliates. All rights reserved. “VERNOVA” is a registered trademark of GE Vernova. “GE VERNOVA” is a registered trademark of GE Aerospace exclusively licensed to GE Vernova. The terms “GE” and the GE Monogram are trademarks of GE Aerospace and are used with permission. 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.