Date: Thursday, May 17, 2018 at 1:00 p.m. ET
Free to attend
Length: Approximately one hour
The increased use of artificial intelligence (AI) and machine learning (ML) techniques such as deep learning is creating a myriad of both challenges and opportunities for enhancements in manufacturing in terms of improved capacity, quality, and efficiency. The semiconductor industry poses somewhat unique challenges arising from its complex, high precision and highly dynamic production environment. One key way that these challenges are being addressed in semiconductor is by using an approach called “computational process control” or “CPC” in which AI and ML are combined with subject matter expertise to provide higher quality analytical solutions. This webcast will look at the AI/ML explosion, what it means to the semiconductor industry, and how CPC is being used to enhance the benefits of these analytical techniques.
What You’ll Learn:
- Learn how AI and machine learning can help semiconductor manufacturers improve capacity, quality, and efficiency.
- Find out why the semiconductor industry poses somewhat unique challenges arising from its complex, high precision and highly dynamic production environment.
- Hear about how new computational process control (CPC) techniques, which combine AI, ML and subject matter expertise, provide higher quality analytical solutions.
Dr. James Moyne is a consultant for standards and technology in the Applied Global Services group at Applied Materials. He received his Ph.D. degree from the University of Michigan, where he is currently an associate research scientist in the Department of Mechanical Engineering. James has been involved with machine learning solutions for the semiconductor industry since the early 90s starting with his founding of MiTeX Solutions, Inc. in 1995, which provided the first 3rd party advanced process control solutions for semiconductor manufacturing. He has experience in advanced process control, prediction technology (predictive maintenance, virtual metrology, and yield prediction), and big data technology (focusing on machine learning and data quality); and is the author of a number of refereed publications and patents in these areas. James is currently chair of the Factory Integration Technical Working Group of the International Roadmap for Devices and Systems, and is technical chair of the annual Advanced Process Control conference for the microelectronics industry (www.apcconference.com).
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