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 image data and create learning-based models, model verification and Applicaiton to nanomechanical switch fabrication and finally cover 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 

Course Duration

45 minutes

Target Audience 

Managers, supervisors, engineers, technicians, or any individual working directly with this equipment or product  

Requisite Knowledge 

None