Industrial AI Podcast cover image

Industrial AI Podcast

How Zeiss engineers use the Markov Chain

Sep 28, 2022
Discover how Zeiss engineers leverage Markov chains to enhance lens production efficiency. The conversation dives into innovative AI-based automation in industrial settings and the ongoing challenges of real-time applications. Explore the significance of predictive quality analytics in manufacturing, as well as the importance of data organization in optimizing processes. The hosts highlight the dual nature of AI while advocating for responsible practices. Plus, insights into strategic alliances in the semiconductor industry keep the dialogue engaging.
37:17

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Quick takeaways

  • Zeiss utilizes Markov chains to model production processes, enabling predictive analytics to improve quality and reduce lens defect costs.
  • The podcast emphasizes the significance of data quality and accessibility in AI-driven engineering for enhanced production efficiency and decision-making.

Deep dives

AI in Automation and Production Engineering

A project at the University of Hamburg focuses on AI-based automation for both virtual and real production environments. The initiative, led by Professors Oliver Niggemann and Alexander Frey in collaboration with DTEK and Weidmüller, aims to develop an open, expandable engineering platform to integrate AI into industrial processes. This platform is expected to address the significant challenges that arise when implementing AI in engineering for automated systems. The goal is to achieve greater efficiency and adaptability in production environments by leveraging AI technologies.

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