Proficy CSense
4 mins
In this demonstration we'll see how a process engineer can reduce process variations using Proficy CSense and the CSense continuous troubleshooter connected to Proficy Historian feeding time-series data.
You will see how to identify the root cause of temperature variation in a furnace by looking at correlations and analyzing key parameters, in this case the anode temperature and create a digital model that you can deploy in production for real time control & analysis.
Predict future asset and process performance
Return to the Proficy CSense page.
Learn how Fibo gained insight to improve quality in just hours by using Proficy CSense analytics software in conjunction with MES and Historian data.
Learn how a global manufacturer used Digital Twin technology to optimize energy efficiency and reduce net energy consumption.
Learn how Skjern Paper uses Industrial AI and Digital Twin technology to monitor and predict process variation and improve product quality.
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