Jay Lee - Industrial AI Augmented Prognostics of Highly Connected and Complex Industrial Systems скачать в хорошем качестве

Jay Lee - Industrial AI Augmented Prognostics of Highly Connected and Complex Industrial Systems

Speaker: Jay Lee, Clark Distinguished Professor and Founding Director of Industrial AI Center, University of Maryland Talk Abstract: 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 intelligent metrology systems including digital twin-based analytics and advanced Stream-of-Quality (SoQ) technologies for different industrial systems including high-volume manufacturing, networked EVs, and wind turbine systems, 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. About the event: Organized by the 2022 cohort of U-M Schmidt AI in Science Fellows. Faculty members, researchers, and trainees joined MIDAS for a day of insightful presentations and discussions on the latest trends and developments in AI for science and engineering. To explore the event program and learn more about the speakers, please visit the event webpage at https://midas.umich.edu/ai-in-science....