Christoph Maier

Failure Analysis (FA) is critical for fast time-to-market and semiconductor reliability, yet structuring FA knowledge to align with FAIR principles (Findable, Accessible, Interoperable, Reusable) remains a challenge. Inspired by medical ontologies, we propose a Failure Analysis Ontology (FAO) to represent FA knowledge in a machine- and human-readable format. This enables knowledge graphs that support AI-driven searches and analytics, delivering faster and more accurate insights across the FA process.

The FAO spans the entire FA workflow, linking FA data with production information such as technology details and FA equipment. This unified framework ensures traceability, smarter analysis, and streamlined problem-solving throughout the semiconductor lifecycle.

As part of the EU-funded FA2IR project, we collaborate with European semiconductor manufacturers, FA service providers, and tool suppliers to create a modular, open-source FA ontology. It includes an open-source base and a standardized proprietary extension, enabling secure internal data integration. Shared failure codes and standardized datasets ensure interoperability and boost FA efficiency across the industry.

I am Christoph Maier, a Failure Analysis Engineer at Infineon Technologies, bringing approximately six years of experience in the semiconductor industry, with a primary focus on analyzing power ICs for automotive applications. I have an academic background in physics and earned a PhD specializing in nanophysics and plasmonics previously.

In recent years, I have been exploring the potential of artificial intelligence to enhance the efficiency of failure analysis processes within both Infineon and also on a European level collaborating with other semiconductor companies and tool suppliers.