About
Smart manufacturers are realizing that industrial AI is only as powerful as the data you provide it. Real-time industrial process data is at the core of effective predictive modeling, and the quality of this data is essential to achieving reliable outcomes. A well-planned data architecture enables intelligent technology to anticipate production failures and provide meaningful recommendations for improved efficiency. This webinar explores what it truly means to build an AI-ready data ecosystem by uncovering common pitfalls and providing solutions you can use to accelerate your plant’s digital maturity.
When
Tuesday, October 14, 2025 · 2:00 p.m. Eastern Time (US & Canada) (GMT -4:00)
Agenda
  • What a Healthy Data Ecosystem Looks Like
  • Where Most Manufacturers Fall Short
  • Real-World Example of Predictive Maintenance
  • What’s Next: Preparing for the Future of Industrial AI
Presenters
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Scott Kahre
Sales Engineer; dataPARC
Scott Kahre is a chemical engineer with over 20 years of experience in process optimization, control, and data analysis. Scott was formerly a dataPARC customer with Amalgomated Sugar and became a sales engineer in 2023 where he helps customers make the most of their industrial analytics solutions and improve performance with valuable process insights.
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Mary Page Bailey
Senior Editor, Chemical Engineering magazine
Mary Page Bailey has been an editor with Chemical Engineering since May 2013, after working five years as a process design engineer at ExxonMobil Chemical Company’s joint venture, Univation Technologies, LLC. During her time with Univation, she designed equipment for numerous Unipol polyethylene plants and attended a plant startup in China. She holds a B.S. Ch.E. degree from the University of Oklahoma.
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