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Mr. Jason Shields

 

 

Mr. Jason Shields

Vice President

Lam Research

 Education:

  • MBA from Santa Clara University

  • B.S. degree in physics from Texas A&M University

 Experiences:

  • Vice President of Integrated Metrology at Nanometrics

  • Vice President of Brion Fab Products at ASML

  • Holding various technical marketing and program manager positions at KLA-Tencor

 Biography:

 

  • Jason Shields is Lam Research vice president of Advanced Equipment and Process Control, where he oversees company strategy for this important area across all product lines. Prior to joining Lam in 2015, he was vice president of Integrated Metrology at Nanometrics. Earlier, he served as vice president of Brion Fab Products at ASML and held various technical marketing and program manager positions at KLA-Tencor. He began his career working in the areas of process, process integration, and yield enhancement at semiconductor manufacturer Advanced Micro Devices. Mr. Shields earned an MBA from Santa Clara University and a B.S. degree in physics from Texas A&M University.

 

 Abstract:

 

  • The concepts of advanced equipment control and advanced process control have been around for many years. These concepts are gaining new life as we enter the age of machine learning, artificial intelligence, and big data with a promise of process equipment achieving both higher productivity at a lower cost and improved process performance. Achieving this vision of equipment intelligence will require strong collaboration between customers and suppliers to innovate in many areas. Collecting relevant, high quality data is the first and most important requirement. This means having the right sensors in the right place, providing easily configurable access to relevant data and a highly reliable infrastructure to ensure data quality without impacting tool performance. Process tool architectures must evolve to support both local on-tool control loops and fab-wide control loops. Flexibility is critical for allowing customers in different environments with different requirements to implement control algorithms. Finally, customer data access protocols will also need to change as closer integration between fab-wide data and local data is required to train control loops. Enabling equipment intelligence at the point of use will require data transparency with collaboration between customers and suppliers. Lam Research is leading the industry into this new era of equipment intelligence by using machine learning, artificial intelligence, and big data, combined with Lam’s equipment and process expertise, to deliver improved productivity and process performance. 

 

 

 

 

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