AI in Prognostics and Health Management

This presentation will illuminate the role and pitfalls that AI plays in Prognostics, one of the most important aspects of Predictive Maintenance. To that end, different techniques for accomplishing the predictive step will be explored in conjunction with advice from fielding them for different industrial applications.

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Bio

Kai Goebel – Principal Scientist | Palo Alto Research Center (PARC)

Kai Goebel is a Principal Scientist in the System Sciences Lab at Palo Alto Research Center  (PARC). His interest is broadly in predictive maintenance and systems health management for a broad spectrum of cyber-physical systems in the manufacturing,  energy, and transportation sectors. Prior to joining PARC, Dr. Goebel worked at NASA Ames Research Center and General Electric Corporate Research & Development center. At NASA, he was a branch chief leading the Discovery and Systems Health tech area which included groups for machine learning, quantum computing, physics modeling, and diagnostics & prognostics. He founded and directed the Prognostics Center of Excellence which advanced our understanding of the fundamental aspects of prognostics. He holds 18 patents and has published more than 375 papers, including a book on Prognostics. Dr. Goebel was an adjunct professor at Rensselaer Polytechnic Institute and is now adjunct professor at Lulea Technical University. He is a member of ASME IEEE, SAE, AAAI; co-founder of the Prognostics and Health Management Society; and associate editor of the International Journal of PHM.