Cluster of Excellence Internet of Production
As the basis for the transfer of Aachen production technology into the age of the fourth industrial revolution, the next important milestone for the further creation of application-oriented and innovative solutions in the field of production technology is now on the agenda of the new Cluster. The IoP offers real-time, secure information availability of all relevant data at any time, at any place and is regarded as the core of industry 4.0. In this way, the IoP paves the way for a new era of production.
Research staff
- Arnab Chakrabarti, M.Sc.
- Lars Gleim, M. Sc.
- Prof. Dr. Matthias Jarke
- Dipl.-Medieninf. István Koren
- Stefan Braun, M. Sc. RWTH
Job openings
Theses
- A Peer-to-Peer Service Framework With WebAssembly (Open)
- Best Practice Sharing in Production Networks (Open)
- Celsius or Fahrenheit? Interoperable Machine Learning for the Internet of Production Using Semantics (Open)
- Datenstromverarbeitung an der Industriemaschine mit WebAssembly – Data Stream Processing on the Edge With WebAssembly (Open)
- Predictive Modelling for High Pressure Die Casting Processes Using High Dimensional Feature Selection (Open)
- A Distributed Data Revisioning System for the Internet of Production (Running)
- A Neural Network Model for Visualization Recommendation System (Running)
- A Visualization Recommendation Tool for Production Systems (Running)
- An Extensible Web Interface for Linked Data Platform Servers (Running)
- Authenticity, Integrity and Trust for Data Reuse in Resource Oriented Architectures (Running)
- Automatic HyperGraphQL Bootstrapping for Triplestores (Running)
- Automatic Provenance Generation for Serverless Computing (Running)
- Autonomous Planning of Industrial Processes for the Internet of Production (Running)
- Development of a WebApp for the User-friendly Tracking of Manufacturing Processes (Running)
- LD-FUSE: A Filesystem in Userspace for the Linked Data Platform (Running)
- Messung der Oberflächenqualität von Vliesflor mittels Feature Extraction (Running)
- Personalizing the User Interface of Requirements Bazaar (2020)
- Automated Semantic Data Labeling using Deep Learning (2019)
- Feature Clustering and Visualization of High Dimensional Data using Clique Cover Theory (2019)
Publications
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FactDAG: Formalizing Data Interoperability in an Internet of Production
Lars Gleim, Jan Pennekamp, Martin Liebenberg, Melanie Buchsbaum, Philipp Niemietz, Simon Knape, Alexander Epple, Simon Storms, Daniel Trauth, Thomas Bergs, Christian Brecher, Stefan Decker, Gerhard Lakemeyer, Klaus Wehrle
Published in IEEE Internet of Things Journal
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Towards an Infrastructure Enabling the Internet of Production
Jan Pennekamp, René Glebke, Tobias Meisen, Christoph Quix, Rihan Hai, Lars Gleim, Philipp Niemietz, Maximilian Rudack, Simon Knape, Alexander Epple, Daniel Trauth, Uwe Vroomen, Thomas Bergs, Christian Brecher, Andreas Buhrig-Polaczek, Matthias Jarke, Klaus Wehrle
Published in Proceedings of the 2nd IEEE International Conference on Industrial Cyber-Physical Systems (ICPS '19), May 6-9, 2019, Taipei, TW , page 31-37. Publisher: IEEE, May 2019
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Security Considerations for Collaborations in an Industrial IoT-based Lab of Labs
Jan Pennekamp, Markus Dahlmanns, Lars Gleim, Stefan Decker, Klaus Wehrle
Published in Proceedings of the 3rd IEEE Global Conference on Internet of Things (GCIoT '19), December 4–7, 2019, Dubai, United Arab Emirates Publisher: IEEE, December 2019
