Recent Advances of Industrial AI for Highly Connected Manufacturing Systems

Industrial AI is a systematic discipline which focuses on developing, validating, and deploying various machine learning algorithms for industrial applications with sustainable performance. According to a recent study report from National Academy of Engineering, the key issues to successfully develop and deploy AI for industrial applications including the lack of good quality of data as well as lack of systematic approach in developing and validating AI.

This presentation will give an introduction about recent advances of digital twin and Industrial AI for highly complex engineering systems. First, Industrial AI systematic approach will be introduced. Case studies on lessons learned from the diversified industrial systems including semiconductor manufacturing, wind farm, electrification, and healthcare/medical systems, etc. will be given.

In addition, issues data quality and training industrial AI skills through data foundry for high performance and

real-time data analytics in future talents will be discussed.