Abstract

Artificial Intelligence (AI) has the potential to simplify complex tasks in industrial asset management, such as predicting equipment failure based on vibration data. This presentation aims to demystify how AI can help even those with little technical training better manage machinery and reduce downtime. We will not only explore how AI can help predict, identify, and rectify defects in equipment, but we will also delve into how Explainable AI (XAI) concepts can be used to help users understand and trust an AI’s decisions.

Presenter

Dr. Andy Zimmerman

Chief Technology Officer – Grace Technologies

Andy, is a pioneer in wireless sensing and cloud-based monitoring systems, with a background in civil infrastructure and industrial machinery. Holding a Ph.D. in Civil Engineering and an M.S.E. in Computer Science & Engineering, he founded Civionics in 2009, which later integrated its technologies into Grace Technologies in 2018. At Grace, Dr. Zimmerman leads the engineering department and has been instrumental in developing the GraceSense line of Predictive Maintenance and Industrial Internet of Things technologies.