The fourth industrial revolution dramatically increased the number IIoT sensors present in chemical manufacturing, corresponding to a wealth of time-series process data. Advanced analytics software applications like Seeq have become transformational in organizations, leveraging this wealth of data and turning information to insight. Seeq’s low-to-no-code environment empowers process subject matter experts (SMEs) to apply advanced statistics and machine learning concepts to data from any of their connected historian or contextual data sources. Using Seeq has empowered SMEs in Ethylene production facilities to solve many previously unsolvable use cases. The use cases covered in this presentation will include: Analysis of Furnace De-cokes, Heat Exchanger Maintenance Prediction, Modeling Downstream Quality Parameters from Upstream in-process Data, and Advanced Asset Monitoring.
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