SEMI105 AI-Enhanced Microfabrication of Printed Electronics

Course Description This course will teach the material needed to connect cleanroom and printed electronics science and technology to advanced data processing capabilities that Artificial Intelligence and Machine Learning can enable. Cleanroom tools inherently have millions of internal variables and can learn from the datasets, providing a robust and complementary approach to traditional feedback control and process stabilization approaches. Learning models are developed on images, time history data, and textual process information. A subset of the class will include Approaches to pre-process image data and create learning-based models, Model Verification, Application to nanomechanical switch fabrication and Cloud-based implementation, data security, and data standardization.  Learning models are developed on images (CD-SEMS, optical images), time history data (Optical Emission Spectroscopy), and textual process information.  A subset of the class will include Approaches to pre-process