This project investigates the algorithms used in current technology Integrated Circuit (IC) Inspection and Defect Classification methods in search of room for improvement. IC Inspection is of a vital importance for chip manufacturing companies to act upon various sources of error in IC fabrication processes, providing the type and cause of errors during run-time or offline data processing stages. This enables fast re-alignment and/or correction of the fabrication processes, cutting down significantly the cost of defective manufacturing. 

The IC inspection for defects is done by identifying the defect areas, analyzing the defects to extract representative information, and grouping them based on the extracted information to identify the process stage that needs to be corrected of malfunctions. 

In this token, the project focuses on better defect representation and classification methods via signal processing and pattern recognition techniques that promise to enhance IC inspection performance that would allow faster and more accurate respond to error sources occurring in the manufacturing process.

Contact wes@eos.ncsu.edu for more information