Machine learning assisted signal analysis in Acoustic Microscopy for non-destructive defect identification

Monday, November 11, 2019: 4:25 PM
F 150/151 (Oregon Convention Center)
Mr. Michael Kögel , Fraunhofer Institute for Microstructure of Materials and Systems IMWS, Halle, Germany
Dr. Sebastian Brand , Fraunhofer Institute for Microstructure of Materials and Systems IMWS, Halle, Germany
Mr. Frank Altmann , Fraunhofer Institute for Microstructure of Materials and Systems IMWS, Halle, Germany

Summary:

The paper describes the application of machine learning based algorithms onto time resolved echo signals obtained by acoustic microscopy (SAM) for the identification of defects in flip-chip interconnects.
See more of: 3D Device Failure Analysis II
See more of: Technical Program