Fraunhofer Institute for Microstructure of Materials and Systems IMWSThe use of machine learning can improve signal processing and thus enable more accurate results in high-resolution, non-destructive defect localization in microelectronic components. Dr. Sebastian Brand from the Fraunhofer Institute for Microstructure of Materials and Systems IMWS presented findings and application examples of these possibilities at the 49th International Symposium for Testing and Failure Analysis (ISTFA) in Phoenix / USA in November. His contribution has now been honored as "Attendees Best Paper" at the international symposium.
Almost 800 participants attended the five-day conference, which is one of the world's most important specialist meetings for fault diagnostics in microelectronics. At the end of the conference, prizes were awarded in seven categories, and the Fraunhofer IMWS was doubly successful. In addition to the paper "Advances in High-Resolution Non-Destructive Defect Localization based on Machine Learning Enhanced Signal Processing" by Sebastian Brand, to which Michael Kögel, Christian Große and Frank Altmann also contributed from the Fraunhofer IMWS, Susanne Hübner also won an award. She was recognized at the conference for the best black and white image related to fault diagnostics.
In total, the Fraunhofer IMWS was represented with three tutorial presentations and five lectures in the conference program, which this year focused on new technologies and the corresponding error analysis in the field of power electronics.
"Our contributions met with a lot of interest and a very good response. The two awards, for which I warmly congratulate Sebastian Brand and Susanne Hübner, are a nice confirmation of this," says Frank Altmann, Head of the "Materials and Components for Electronics" business unit at the Fraunhofer IMWS, who also served as General Chair of the ISTFA this year. "Artificial intelligence methods are becoming increasingly important for failure analysis and material characterization. I am delighted that our expertise in this area has been recognized by a top-class international community with this award."