About This Course
Course Description
This course provides the knowledge needed to integrate cleanroom and printed electronics science with the advanced data processing capabilities enabled by Artificial Intelligence and Machine Learning. Cleanroom tools contain millions of internal variables and can leverage datasets for a robust, complementary approach to traditional feedback control and process stabilization. Learning models are developed using images (e.g., CD-SEMS, optical images), time history data (such as Optical Emission Spectroscopy), and textual process information.
The course will cover methods to preprocess image data, build learning-based models, verify models, and apply these techniques to nanomechanical switch fabrication. Additionally, it addresses cloud-based implementation, data security, and data standardization.
Course Objectives
- Topics covered will include the following: Introduction to AI in microfabrication and printed electronics, Fabrication and Data Collection, Data and Image Processing, AI and Machine Learning Algorithms, Results, and Outlook
Target Audience
- Managers, supervisors, engineers, technicians, or any individual working directly with this equipment or product
Your Instructors
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