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Holger-Brandl-Systema-inno23

Holger Brandl

Team Manager & Project Manager
SYSTEMA

AND Breakout-Sessions
Breakout: Ensuring Data Integrity in Semiconductor Manufacturing to Unlock the Power of Automation, Digital Twin and AI

In semiconductor manufacturing, the effectiveness of automation, digital twins and AI is highly dependent on the quality of the data they rely on. Poor data quality can lead to production errors, inefficiencies, and non-compliance – challenges that even advanced systems struggle to overcome without clean, reliable data. This breakout session, hosted by SYSTEMA, will explore the critical role of data integrity and data management in preventing the “garbage in, garbage out” (GIGO) problem.

The session will provide practical insights into maintaining robust data management, with guidance on proactively validating data, improving traceability, and preparing systems for the future of AI-driven automation. Attendees will gain a structured approach to ensuring data integrity in an increasingly complex, data-driven industry.

We will discuss real-world examples of how Advanced Planning and Scheduling (APS) solutions can leverage event-driven architecture and real-time data readiness to support complete line- or fab-wide schedules, predictive manufacturing, and forecasting for bottleneck and/or delivery date prediction. Join us to learn how maintaining seamless data flow is not just a technical requirement but a fundamental step toward unlocking the full potential.

About Holger Brandl

Holger Brandl is an analytics solution architect at SYSTEMA (Dresden, Germany) where his work is focused around developing machine learning and cloud solutions for Industrial IoT and analytics. His commitment to revealing patterns in large unstructured data sets leads to quick and efficient delivery of actionable insights.

The open-source tools, methods and algorithms he develops for factory optimization, high-performance computing, and data science are aligned with and supported by the latest technology and science.

He holds a Ph.D. in machine learning, has developed novel concepts in computational linguistics, and recently co-authored systems biology publications in high-ranking journals including Nature and Science.