Smart Architectures (SmArt)

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.

Smart Architectures Pyramid — Overview "Smart Architectures" Group

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
Testing theorethical approaches in the Process-to-Order Lab doi.org/10.2139/ssrn.4456423

Teaching

Research Projects

The Team

Research Assistant

Mr Dipl.-Ing. Lucas Vogt

Team Lead - Smart Architectures Group

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Professur für Prozessleittechnik Arbeitsgruppe Systemverfahrenstechnik

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Visiting address:

Merkelbau, MER/12A Helmholtzstraße 14

01069 Dresden

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Further Information

Group lead:

Dipl.-Ing. Lucas Vogt

Group members:

Zohra Charania M.Sc.

Dipl.-Inf. Norman Trapp

Dipl.-Ing. Xinyu Wang

Former group members:

Dr. Ilhan Mutlu

Fatima Rani M.Sc.

Publications

41 Entries

2024

Strategies for Software and Hardware Compatibility Testing in Industrial ControllersRothhaupt, M., Vogt, L. & Urbas, L., 14 Mar 2024, In: Processes : open access journal. 12 (2024), 3, 14 p., 580Electronic (full-text) versionResearch output: Contribution to journal > Research article
Strategies for Software and Hardware Compatibility Testing in Industrial ControllersRothhaupt, M., Vogt, L. & Urbas, L., 31 Jan 2024, MDPI, BaselElectronic (full-text) versionResearch output: Preprint/documentation/report > Preprint

2023

CNN-basierte Detektion von Geometriefeatures auf Grundlage diskreter VoxeldatenVogt, L., 10 Dec 2023, 91 p.Electronic (full-text) versionResearch output: Types of Thesis > Diploma thesis
Towards cloud-based Control-as-a-Service for modular Process PlantsVogt, L., Klose, A., Khaydarov, V., Vockeroth, C., Endres, C. & Urbas, L., 12 Sep 2023, 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA). Sinaia, Romania: Institute of Electrical and Electronics Engineers (IEEE)Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Anforderungen an die zukünftige Prozessautomation in der Biopharma-IndustrieVogt, L., Klose, A., Mutlu, I. & Urbas, L., 27 Jun 2023, Automation 2023 - 24. Leitkongress der Mess- und Automatisierungstechnik: Transformation by Automation. VDI Verlag, Düsseldorf, p. 943-958, 16 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
P2O-Lab: A Learning Factory for Digitalization and ModularizationVogt, L., Pelzer, F., Klose, A., Khaydarov, V., Lange, H., Viedt, I., Mädler, J. & 1 others, 23 May 2023Electronic (full-text) versionResearch output: Contribution to conferences > Paper
Enhancing 3D-CNN-based Geometric Feature Recognition for Adaptive Additive Manufacturing: A SDF Data ApproachHilbig, A., Vogt, L., Holtzhausen, S. & Paetzold, K., 4 Apr 2023, In: Journal of Computational Design and Engineering. 10, 3, p. 992-1009, 18 p.Electronic (full-text) versionResearch output: Contribution to journal > Research article
Anomaly Detection in Chemical Processes with Semantic Knowledge Graphs: An Approach to Reduce Cause-Effect DiagramsHamedi, N., Mutlu, I., Rani, F. & Urbas, L., Jan 2023, 33rd European Symposium on Computer Aided Process Engineering. 6 p.Electronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
A Centralized MongoDB Based Repository Design for IIoT Data : The ecoKI ProjectRani, F., Wang, X., Mutlu, I. & Urbas, L., 2023, 22nd IFAC World CongressElectronic (full-text) versionResearch output: Contribution to book/conference proceedings/anthology/report > Conference contribution
Advancing with digitalization and AI for energy and cost efficiency for SMEs: ecoKI perspectiveRani, F., Khaydarov, V. & Urbas, L., 2023Electronic (full-text) versionResearch output: Contribution to conferences > Poster