Innovation in Failure Analysis and Material Diagnostics of Electronics Components

4th and 5th June 2024

Halle, Germany

The registration deadline has passed.

We regret that we are unable to accept any further registrations for the CAM Workshop 2024 at this time.

Technical Topics

We would like to thank our sponsors


Dear colleagues,

we are delighted to invite you to the 11th CAM-Workshop on „Failure Analysis and Material Diagnostics of Electronics Components“ on 4th and 5th June 2024.

As usual, the CAM-Workshop will bring together experts from the electronics industry and material diagnostics equipment manufacturers. The goal is to discuss challenges, innovative solutions, and future requirements in the field of failure analysis and material characterization of electronic devices, sensors, and systems.

In addition to the scheduled oral presentations, there will be an industrial exhibition featuring suppliers of failure analysis and material diagnostics equipment. This unique concept allows for direct interaction between electronics failure analysis experts and diagnostics equipment manufacturers. It has helped establish the CAM workshop as an internationally recognized event and a hub for failure diagnostics in electronics.

We are excited to welcome all of you to Halle next June.

Frank Altmann

on behalf of the CAM-Workshop committee

Meet our CAM-Workshop Committee


Frank Altmann

Fraunhofer IMWS (Germany)

Ingrid De Wolf

IMEC and KU Leuven (Belgium)

Pascal Gounet

STMicroelectronics (France)

Joerg Krinke

Robert Bosch GmbH (Germany)

Thomas Schweinboeck

Infineon Technologies AG (Germany)

Szu Huat Goh

Qualcomm (Singapore)

Eckhard Langer

Infineon Technologies AG (Germany) representing Eufanet

Information about our partnering conference

ISTFA 2024

Artificial Intelligence (AI) is revolutionarily changing the world, and profoundly reshaping the semiconductor industry. AI has been integrated into design, manufacture, process optimization, quality, reliability, and failure analysis (FA). Embracing and effectively using AI in Fault isolation (FI) and FA becomes crucial for new technology development  and high-volume mass production in semiconductor industry. Although numerous AI applications in FI and FA have been demonstrated, there are still many unaddressed challenges, unestablished standards, and unexplored applications to be resolved. On the other hand, giant and highly integrated high-performance computing devices designed for AI algorism training lead to tremendous challenges to FI and FA.