Webinar: AI-supported fault analysis & yield optimization in semiconductor manufacturing

In semiconductor manufacturing, even seconds can translate into millions in value. Yet, crucial information for error analysis is often scattered across diverse systems. Our Multi-Agent Knowledge Retrieval System intelligently integrates these heterogeneous data sources to enable comprehensive analysis of complex error scenarios. This empowers manufacturers to achieve full transparency, minimize downtime, and significantly increase yield.

Why should you participate in the webinar?
Join this webinar to discover how advanced AI techniques such as Retrieval-Augmented Generation (RAG), Source Grounding and AI Agents are used to identify complex root causes of errors and drastically reduce AI hallucinations. This approach enhances the safety and reliability of your manufacturing processes.

Key Take Aways

Faster root cause analysis for complex failure scenarios
Less manual research, lower susceptibility to errors
Improved yield stability in high‑volume / high‑precision manufacturing
Better decision-making basis for engineering and operations

Referent:

Philipp Gersten AI Engineer, ZEISS Digital Innovation

Philipp Gersten develops AI architectures for the semiconductor industry based on multi-agent systems with strict requirements for factual accuracy and verifiability. His focus is on robust, auditable GenAI services with RAG, deterministic orchestration, and end-to-end evaluation and operational monitoring. With over eight years of experience in Python, SQL, and modern LLM/ML stacks, he combines technical excellence with clear communication and reliable implementation for measurable business benefits, improved processes, and reliable teamwork. He holds an M.Sc. in Professional IT Business and a B.Sc. in Business Informatics.