Smart Architectures

Introduction

The Smart Architectures team focuses on new methods and approaches to lay the foundations for flexible, efficient and reliable cyber-physical production systems of the future through architectural concepts. In particular, the increasing requirements regarding time-to-market, quality, flexibility, reliability and complexity handling are incorporated into the research.

Research Focus

How can automation architectures be future-proofed for Industry 4.0 and beyond in the process, manufacturing and pharmaceutical industries?
How can the use of advanced automation methods such as artificial intelligence, machine learning or model predictive control be enabled or facilitated in industry through suitable system architectures?
How can novel measures and applications be designed to ensure the quality, stability and integrity of the data generated in Industry 4.0?
How can new methods and approaches be implemented to enable more efficient data acquisition, storage and processing in an industrial context?

Innovative Methods and Tools

Scenario techniques for requirements elicitation doi.org/10.51202/9783181024195
Smart automation architectures doi.org/10.1109/ETFA.2019.8869439
Technologieanalysen doi.org/10.1109/ITNAC55475.2022.9998327
Concept development for data-driven industrial applications FIS TU Dresden
Testing theorethical approaches in the Process-to-Order Lab doi.org/10.2139/ssrn.4456423

Teaching

Research Projects

The Team

Doctoral Researcher

Mr Dipl.-Ing. Lucas Vogt

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Process Systems Engineering Group

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Visiting address:

Barkhausenbau, MER/12A Helmholtzstraße 18

01069 Dresden

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Group lead:

Dipl.-Ing. Lucas Vogt

Scientific Staff:

Dipl.-Ing. Xinyu Wang

Fatima Rani M.Sc.

Zohra Charania M.Sc.

Former scientific staff:

Dr. Ilhan Mutlu

Publications

30 Entries

2024

IIoT Data-Driven Analytics Pipeline for Industrial Process EngineeringRani, F., Vogt, L. & Urbas, L., 11 Nov 2024Research output: Contribution to conferences > Poster
Bringing Human Cognition to Machines: Introducing Cognitive Edge Devices for the Process IndustryCharania, Z., Vogt, L., Klose, A. & Urbas, L., 17 Aug 2024, Proceedings of the 22nd IEEE International Conference on Industrial Informatics (INDIN). IEEE Xplore, 7 p.Research output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Far vs. Near: A Decision Framework for Cloud and Edge Use in the Process IndustryVogt, L., Charania, Z. & Urbas, L., 17 Aug 2024, Proceedings of the 22nd IEEE International Conference on Industrial Informatics (INDIN). IEEE Xplore, 8 p.Research output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Containerisierung von Model Predictive Control für modulare Anlagen: Ein Schritt zu intelligenten Edge Systemen Charania, Z., Vogt, L., Badrnoebashar, H., Koch, A., Lorenz, J., Mädler, J. & Urbas, L., 2 Jul 2024, Automation 2024: 25. Leitkongress der Mess- und Automatisierungstechnik (AUTOMATION 2024) ;AI beats Automation?. 1 ed., VDI Verlag, Düsseldorf, p. 33-45, 14 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Demonstration von “Industrial Control as a Service” für Biopharma-AnwendungenVogt, L. & Urbas, L., 2 Jul 2024, Automation 2024: 25. Leitkongress der Mess- und Automatisierungstechnik (AUTOMATION 2024) ;AI beats Automation?. 1 ed., VDI Verlag, Düsseldorf, p. 485-496, 12 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Scalable data pipeline: Ontology-based OPC UA data access for the industrial internet of thingsRani, F., Wang, X., Charania, Z., Vogt, L. & Urbas, L., 2 Jul 2024, Automation 2024 : 25. Leitkongress der Mess- und Automatisierungstechnik (AUTOMATION 2024) ;AI beats Automation?. 1 ed., VDI Verlag, Düsseldorf, p. 419-434, 16 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Steigerung der Energieeffizienz für eine nachhaltige Entwicklung in der Produktion: Die Rolle des maschinellen Lernens im ecoKI-ProjektWang, X., Rani, F., Charania, Z., Vogt, L., Klose, A. & Urbas, L., 2 Jul 2024, Automation 2024: 25. Leitkongress der Mess- und Automatisierungstechnik (AUTOMATION 2024); AI beats Automation?. 1 ed., VDI Verlag, Düsseldorf, p. 825-840Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Industrial Edge MLOps: Overview and ChallengesRani, F., Chollet, N., Vogt, L. & Urbas, L., 2 Jun 2024, ESCAPE34-PSE24: European Symposium on Computer Aided Process Engineering and International Symposium on Process Systems Engineering. Elsevier, Berlin [u.a.], Vol. 53. p. 3019-3024, 6 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Demonstrating Containerization of Model Predictive Control for Modular PlantsVogt, L., Charania, Z., Mädler, J., Lorenz, J., Badrnoebashar, H., Koch, A. & Urbas, L., 12 May 2024, Proceedings of the 2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS). St. Louis: IEEE Xplore, 6 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Strategies for Software and Hardware Compatibility Testing in Industrial ControllersRothhaupt, M., Vogt, L. & Urbas, L., 14 Mar 2024, In: Processes : open access journal. 12, 3, 580Electronic (full-text) versionResearch output: Contribution to journal > Research article