Generalization of Human-Centered AI Applications for Production Optimization

07/09/2021

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Oliver Petrovic

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+49 241 80 27456

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In the New Research Project "GeMeKI", a Broad Consortium is Researching on the Use of Transferable, Human-Centered AI Applications for Production Optimization

  Man with roboter Copyright: © Campus GmbH, Foto: Moll In systems with hybrid intelligence, the competences of humans and artificial intelligence are combined in a synergetic way

The increasingly growing demand for diversity of product variants, quality and sustainability poses enormous challenges for the manufacturing technology of German companies. Artificial intelligence (AI) technologies offer great potential to meet these challenges with increases in flexibility, quality and productivity. Due to the high requirements on data quantity and quality as well as the mostly poor transferability of the solutions, the exploitation of these potentials has so far been limited to stand-alone solutions in large-scale production.

One possible solution lies in the development of transferable systems through the holistic consideration of the key factors of humans, AI and production equipment in human-centered AI applications. The aim of the cooperative project GeMeKI is therefore to explore this approach in order to sustainably improve the performance, flexibility and efficiency of complex manufacturing systems. For this purpose, three use cases of the manufacturing processes joining, cutting and forming are being considered in parallel. In the process, new forms of human-AI interaction, process-related sensor integration and successive data refinement are being developed as the basis of a digital value chain.

  Word cloud Copyright: © WZL A multitude of aspects make GeMeKI a great opportunity for Germany as a manufacting location

The combinatorial view of the triad as an overall learning system gives rise to hybrid intelligence systems in which the complementary strengths of experts and artificial intelligence are combined. On the one hand, AI learns from humans by including them in the training processes of the models. On the other hand, process transparency is significantly increased by processing the data in user-friendly AI assistance systems. Transferring the experience of experts into digital services thus shifts the barrier to entry for tapping the productivity potential of artificial intelligence in the direction of smaller batch sizes.

  Woman at monitor Copyright: © AWK Verein, Foto: Roberto Pfeil To exploit the potential of hybrid intelligence in production, new forms of interac-tion between humans and technology must be developed

At the end of August, the digital kick-off of the research project "GeMeKI" successfully took place under the leadership of the consortium leader aiXbrain and the Laboratory for Machine Tools and Production Engineering WZL of RWTH Aachen University.

Partner in the project "GeMeKI"

  • aiXbrain GmbH
  • Franz Pauli GmbH & Co. KG
  • Fraunhofer-Institut für Produktionstechnologie IPT
  • meastream GmbH
  • Miele & Cie. KG
  • MT Analytics GmbH
  • Siemens AG
  • Starrag Technology GmbH
  • WEISS Spindeltechnologie GmbH
  • Werkzeugmaschinenlabor WZL der RWTH Aachen
  • XENON Automatisierungstechnik GmbH
  • YOUSE GmbH

For more information on the "GeMeKI" research project, please visit the following website: www.gemeki.de.