Industrial AI-Augmented Predictive Methodlogy for Highly Connected and Complex Industrial Systems

J. Lee
Univ. of Cincinnati/Univ. of Maryland,
United States

Keywords: industrial AI, prognostics and health management, industrial internet, IoT, smart manufacturing


Industrial AI, Big Data Analytics, Machine Learning, and Cyber Physical Systems are changing the way we design product, manufacturing, and service systems. It is clear that as more sensors and smart analytics software are integrated in the networked industrial products, manufacturing, and maintenance systems, predictive technologies can further learn and autonomously optimize productivity and performance. This presentation will give an introduction about Industrial AI for smart prognostics systems of highly connected and complex industrial systems. First, Industrial AI systematic approach will be introduced. Case studies on predictive metrology and advanced Stream-of-Quality (SoQ) technologies for different industrial systems including high-volume manufacturing, advanced semiconductor manufacturing, networked EVs, etc, etc. will be given. In addition, issues on data quality for high performance and real-time data analytics in future predictive manufacturing and maintenance will be discussed.