Artificial intelligence is generating significant interest in maintenance and reliability, but many organizations still struggle to translate pilot activity into measurable business results. This presentation is a practical framework for building an AI-enabled condition monitoring program that improves equipment reliability without overwhelming plant personnel, overcomplicating work processes, or creating another disconnected data silo.

What must be true for AI to add value? Rather than starting with algorithms, the presentation starts with equipment criticality, failure modes, baseline condition-monitoring technologies, data quality, alarm rationalization, and workflow discipline.

AI and machine learning can provide value, including anomaly detection, alert prioritization, pattern recognition across multiple asset classes, and identification of hidden relationships between process conditions and mechanical degradation.

The takeaway is a plant-tested roadmap for moving from reactive interpretation of condition data to a scalable, disciplined, AI-supported reliability process.

Buddy Lee (Lloyd Dewey Lee, Jr.) is an executive leader in industrial reliability, condition monitoring, maintenance, and AI-enabled asset performance with more than 25 years of experience serving heavy-asset and power-sector organizations.

He is an Artificial Intelligence and Machine Learning Subject Matter Expert and helps industrial clients apply data contextualization, knowledge graphs, and advanced analytics to improve reliability, operations, and maintenance outcomes. He also serves on the Board of Directors for Appalachian Electric Cooperative.

In July 2023, Lee was appointed to the Fairview Technology Center’s Board of Directors, where he assists technical start-up companies with management and funding issues.

Over the course of his career, he has held engineering, technical, instructional, and business leadership roles, beginning with the U.S. Department of Energy and CSI before founding MAARS, Inc. in 1996. Through MAARS, he helped develop permanently mounted vibration and process monitoring systems and became a co-holder of U.S. Patent No. 6,276,213 for a signal conditioning circuit and hardware used in vibration monitoring. He later served as an instructor with Emerson and has become a recognized speaker on practical AI and machine learning use cases for industry.

Lee holds a BS in Electrical Engineering, an MBA, and a M.S. in Reliability Engineering  from the University of Tennessee and is a Certified Maintenance and Reliability Professional, a Certified Reliability Leader, and a Category III vibration analyst.

In 2024, he was named an adjunct lecturer at the University of Tennessee, where he teaches MRE 484 Introduction to Reliability and Maintenance Engineering.

Buddy grew up in Knoxville and Dandridge, in the summers on Douglas Lake. He lives with his wife, Lisa, in Dandridge. They have two grown children, Adam and Ashley.

For more information on TSK and its meetings, please email TSK secretary, This email address is being protected from spambots. You need JavaScript enabled to view it. or call him at 865-679-9854.