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dan-meier-applied-materials-innovation-forum-for-automation

Dan Meier

Director, MES Product Management
Applied Materials

Speech
Digital Twin: The Centerpiece of Factory AI Transformations

Digital Twin technology is often associated with modeling physical objects, but its transformative power lies in modeling and predicting the performance of the factory that manufactures the physical objects. 

This lecture explores how Digital Twins can be leveraged with Artificial Intelligence to rapidly surface actionable insights into factory metrics such as yield, cycle time, and throughput. Rather than simply presenting another dashboard that shows “what” is happening, a performance-focused Digital Twin enables manufacturers to understand “why” performance issues occur, pinpoint areas needing attention, and visually drill down to root causes. When coupled with AI, a Digital Twin is an ideal platform to enable predictive models that recommend actions to mitigate or prevent future factory performance risks. 

Attendees will learn how integrating real-time data, simulation, and advanced analytics within a Digital Twin framework empowers operations teams to move beyond passive monitoring toward proactive, data-driven decision-making, unlocking new opportunities for continuous improvement and competitive advantage. 

About Dan Meier

Dan Meier is a seasoned manufacturing professional with over 30 years of factory operational and management experience. He has an extensive background in manufacturing optimization, quality systems, analytics, financial modeling, factory automation, and manufacturing software systems. Dan earned a Master of Science in Electrical Engineering and a Master of Business Administration from the University of New Mexico and holds bachelor’s and master’s degrees in music from The Juilliard School.