SiEvEI 4.0

Trusted data acquisition in microelectronics manufacturing as a basis for ML-optimized processing

Trusted data acquisition in microelectronics manufacturing as a basis for ML-optimized processing
© Fraunhofer IZM
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In the digitization of manufacturing processes, one of the major goals is the connection of production facilities and the use of data to digitize business processes. In order to optimize manufacturing processes and maximize the quality of the resulting product, further process information and data directly from the work piece and from the manufacturing environment are required to achieve a holistic system view in addition to the selected data that the manufacturing systems already provide.

Within the SiEvEI 4.0 project, a research consortium from industry and academia works on process digitization for a manufacturing scenario where high value electronic goods are built in a distributed manufacturing environment. The key research topics addressed are the implementation of a Chain of Trust [CoT] for trustworthy distributed manufacturing and the application of artificial intelligence/machine learning to analyze and to eventually optimize manufacturing processes.

The experimental evaluation of these concepts took place in two different assembly lines, including data acquisition, data handling and AI processing with the goal to optimize processing targeting higher production yield and product quality.

To collect environmental data and for PKI based data encryption, specific modules are used – the Secure Sensor Items [SSI]. In the project, manufacturing of these SSIs is used to gather data that is used by ML algorithms to optimize the manufacturing processes.

Project partners

  • Universität Bielefeld
  • Sensorik Bayern GmbH
  • Wagenbrett
  • Siemens
  • WIBU Systems
  • atg Luther & Maelzer

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