Fritzsche

20. May 2026 14:40 – 15:00 Artificial Intelligence and Digitalization Integrated Digital Workflows for Accelerated Failure Analysis and Enhanced Yield Learning in Semiconductor Manufacturing Michael Fritzsche GlobalFoundries Fab1 I Germany Abstract Failure analysis in semiconductor manufacturing requires fast and reliable access to many different data sources. As IT environments continue shifting toward cloud‑based solutions, traditional,…

Heinemann

20. May 2026 14:00 – 14:20 Artificial Intelligence and Digitalization Noise in SAM Data: When Similar Signals Lead to Different Diagnoses Lorenz Heinemann  Fraunhofer IMWS I Germany Abstract Scanning Acoustic Microscopy (SAM) is widely used in semiconductor failure analysis, but interpreting its data remains challenging. In practice, measurement noise, caused by complex packaging structures and…

Svenningsson

20. May 2026 15:20 – 15:40 Artificial Intelligence and Digitalization Federated Learning for Semiconductor Failure Analysis Leo Svenningsson RISE I Sweden Abstract Semiconductor failure analysis increasingly benefits from machine learning, but individual organizations often lack enough data to build robust and accurate models. At the same time, building databases across companies is typically restricted due…

Choudhary

20. May 2026 15:00 – 15:20 Artificial Intelligence and Digitalization Accelerating and standardization of failure analysis through digital workflows and machine learning Amit Choudhary Matworks GmbH I Germany Abstract Failure analysis (FA) in microelectronics is increasingly challenging due to miniaturization and the need for precise defect localization. Traditional methods rely on manual, time-intensive inspection. We…

Fichtl

20. May 2026 14:20 – 14:40 Artificial Intelligence and Digitalization Exploring the value of instance segmentation & other AI methods for Failure Analysis Bernhard Fichtl Carl Zeiss Microscopy GmbH I Germany Abstract Failure analysis increasingly depends on high‑resolution imaging, but extracting quantitative information from large datasets is still manual and slow. This talk explores how…