PI: Zheng Yao
Co-PI(s): Yu Yang
University: Lehigh University
Industry partner: Broadcam, Inc.
The proposed project will investigate and assess the capabilities of artificial intelligence techniques for quality prediction and control in semiconductor wafer manufacturing. As one of the most complex processes in the manufacturing industry, semiconductor manufacturing requires equipment with various control variables. A physical model and expert knowledge are sometimes insufficient to identify all the factors impacting product quality. The existing practice relies on huge amounts of data and microscopic images collected during the manufacturing process. However, most of the testing and analysis results have to be compiled and interpreted manually. This manual process is highly time-consuming and can vary among different personnel, which introduces uncertain prediction results on product quality. To this end, this project will propose a data-driven method based on artificial intelligence techniques to assist the quality prediction and control in the semiconductor wafer manufacturing processes, which, in the long run, will provide the manufacturer with a tool that can be implemented in situ and online.