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ITEA PO Preparation Days 2023

minds.ai attends the 2023 ITEA PO Days

Thrilled to share a glimpse into our journey to transform semiconductor manufacturing! 🚀 We’re all set to participate in the much-anticipated “ITEA PO Preparation Days 2023”, where we’ll be teaming up with Robert Bosch, NXP (pending), Ecole des Mines de Saint-Etienne, IMT Atlantique and FernUni Hagen to present the ‘INTERACTION’ proposal. With this proposal we aim to advance the state-of-the-art in equipment health and wafer quality analysis towards risk-aware scheduling that will increase the chip throughput in a semiconductor fab using AI/ML methods (See below for the full abstract).

Mark your calendars for the event on September 12th and 13th in Berlin. Our minds.ai representative, Abdel, will be on-site, ready to explain more about the proposal. Whether you’re interested in joining this project or simply want to hear more about minds.ai, don’t hesitate to connect with Abdel ahead of or during the event.

For more information about the ITEA event see the official website here.

Here’s to the anticipation of vibrant conversations, groundbreaking ideas, and potential collaborations.

Hope to see you there! 

Integration of Equipment Related-data for Advanced Context-aware Tailored optimisation

Abstract: 

The European Chips Act aims to retain 20% of the market by 2030. Increasing FAB capacity would not be enough. Semiconductors have been so far the digitalisation factor for all the other industries. So far, the digitalisation efforts in semiconductor manufacturing have been sacrificed for the benefit of feeding the demand. This project would like to develop a framework to integrate more data from the equipment data and interact with other systems in the semiconductor manufacturing through AI/ML methods to increase the chip throughput.

Industry Impact:

  • Competitiveness & Profitability: Higher quality and lower waste.
  • Productivity: Higher uptime & efficiency (OEE), faster cycle times, higher yield.
  • Resiliency: Avoid disruptions and flexible production scheduling.
  • Workforce time: Automated insights lead to less manual interventions.
  • Sustainability: Reduce product waste, energy and chemical usage.

Related

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