#Smart Manufacturing

Digitalisation and the Internet of Things increasingly change the production methods and the relationship between humans and machines in Industry 4.0. Research on Smart Manufacturing investigates the application and development of new technologies.

Projects

Josef Ressel Center Industrial Data Lab

Josef Ressel Centre for Knowledge-Assisted Visual Analytics for Industrial Manufacturing Data.

DIHOST 2.0

A platform that brings digital innovations to small and medium-sized companies in Eastern Austria.

Institute of Creative\Media/Technologies

Trust AI - A platform for interactive and trustworthy artificial intelligence.

Explainable and trustworthy AI solution in an easy-to-use platform for SMEs.

ABC - Austrian Blockchain Center

K1 competence center with the goal of the scientifically based further development of the blockchain technology and its application in various economic sectors. These range from Industry 4.0/Internet ...

ECO-TCO

Optimization of product design and configuration for an ecodesign-compliant total cost of ownership approach.

DPP4E

Digital Product-Pass for Electronics.

Institute for Innovation Systems

DPP4Food - Digital product pass for food

Tracking and Tracing along a food supply chain: the soy case

LogiTRAAK

Asset tracking to optimize processes within companies and along the supply chain.

MVPF- Visual Monitoring of Crop Production Systems: A multimodal Approach

Improving imaging techniques that are used to monitor crop production.

Ergo4All – Ergonomics for everyone

An app for analysing work processes and improving them according to ergonomic criteria.

Publications

Rind, A., Blasinger, A., Enge, K., Grassinger, F., Oliveira, V. A. de. J., & Zauchinger, M. (2024, May 24). Wie können wir Daten erlebbar machen? [Demo & Poster]. Lange Nacht der Forschung 2024, St. Pölten. https://langenachtderforschung.at/station/1213

Wagner, M., Böck, A., Größbacher, S., & Rind, A. (2024, May 16). Industrial Data Lab [Poster]. Digitech Corner/AIMS 5.0 General Asssembly, St. Pölten.

Bibtex

Digital Product Pass Concept for a Soy Supply Chain: Solution Design and Data Usage Perceptions. (2024). [Abstract, oral presentation]. 6th IConCMT, FH St. Pölten. https://iconcmt.fhstp.ac.at/

Taurer, F., Widhalm, M., Girsule, B., Rottermanner, G., & Jandl, C. (2023, April). User-Centered Design Guidelines for developing single-purpose apps in an industrial context. 16. Forschungsforum der Österreichischen Fachhochschulen, St. Pölten (Austria). http://ffhoarep.fh-ooe.at/handle/123456789/1736

Baumann, C., & Schlager, A. (2022, June 23). Immersive Storytelling as Knowledge Production in Virtual and Augmented Reality [Präsentation]. Epistemic Media: Atlas, Archive, NetworkNECS 2022 Conference, Bukarest. https://necs.org/conference/

Husinsky, M., Schlager, A., Jalaeefar, A., Schumach, M., & Jacheck, M. (2022, December 3). Situated Visualization of IIoT Data on the Hololens 2. 1st International Workshop on EXtended Reality for Industrial and Occupational Supports (XRIOS). IEEEVR, Online Event.

Bibtex

Wintersberger, M., Baumann, C., Jachek, M., Munk, C., Nagl, A., & Vogt, G. (2021, December 31). Intermedia Motion Tracking in AR/VR – On Immersive Storytelling and Choreographic Patterns. ISSN: 2436-0503 – The Kyoto Conference on Arts, Media & Culture 2021: Official Conference Proceedings. The Kyoto Conference on Arts, Media & Culture 2021, Kyoto, Japan. https://papers.iafor.org/submission61349/

Nurgazina, J., & Felberbauer, T. (2021, November 19). InnoFIT – Information Technologies for Novel Forecasting Tools [Project presentation at the R&D projects dissemination event]. 3rd International Conference on Industry 4.0 and Smart Manufacturing, Online. http://www.msc-les.org/ism2021/program/

Wintersberger, M., & Munk, C. (2021, October 11). Intermedia Motion Tracking in AR/VR – On Immersive Storytelling and Choreographic Patterns. The 2nd Kyoto Conference on Arts, Media & Culture (KAMC2021) [Vortrag mit Diskussion ONLINE]. https://kyoto-amc.iafor.org/

Girsule, B., Rottermanner, G., Jandl, C., & Moser, T. (2021). Machine Learning Support for Repetitive Tasks in Metal Processing SMEs. 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), 1–6. https://doi.org/10/gnhmb2

News

10/10/2024