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Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory

  • Jana-Rebecca RehseEmail author
  • Nijat Mehdiyev
  • Peter Fettke
AI Transfer
  • 18 Downloads

Abstract

With the advent of digitization on the shopfloor and the developments of Industry 4.0, companies are faced with opportunities and challenges alike. This can be illustrated by the example of AI-based process predictions, which can be valuable for real-time process management in a smart factory. However, to constructively collaborate with such a prediction, users need to establish confidence in its decisions. Explainable artificial intelligence (XAI) has emerged as a new research area to enable humans to understand, trust, and manage the AI they work with. In this contribution, we illustrate the opportunities and challenges of process predictions and XAI for Industry 4.0 with the DFKI-Smart-Lego-Factory. This fully automated factory prototype built out of LEGO\(^\circledR\) bricks demonstrates the potentials of Industry 4.0 in an innovative, yet easily accessible way. It includes a showcase that predicts likely process outcomes and uses state-of-the-art XAI techniques to explain them to its workers and visitors.

Keywords

Process prediction Explainable artificial Intelligence Smart factories Industry 4.0 

Notes

Acknowledgements

We gratefully acknowledge the support of NVIDIA Corporation with the donation of the GPUs used for this research.

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Copyright information

© Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Jana-Rebecca Rehse
    • 1
    Email author
  • Nijat Mehdiyev
    • 1
  • Peter Fettke
    • 1
  1. 1.Institute for Information Systems at the German Research Center for Artificial Intelligence (DFKI) and Saarland UniversitySaarbrückenGermany

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