Future Lab Production Networking, Modeling and Optimization of the Industrial Production

被引：0

作者：

Kallisch J. ^{[1
]}

Denkena B. ^{[2
]}

Kramer K. ^{[3
]}

Stürenburg L. ^{[1
]}

Pachandrin S. ^{[4
]}

Rokicki M. ^{[5
]}

Walter J. ^{[6
]}

Nein M. ^{[2
]}

Voss M. ^{[7
]}

Wunck C. ^{[1
]}

Niemann K.-H. ^{[7
]}

Schmidt M. ^{[8
]}

Dilger K. ^{[4
]}

Niederée C. ^{[5
]}

Hoffmann N. ^{[4
]}

机构：

[1] Hochschule Emden/Leer, Constantinplatz 4, Emden

[2] IFW, Leibniz Universität, Hannover

[3] IPTS, Leuphana Universität, Lüneburg

[4] IFS, Technische Universität, Braunschweig

[5] Forschungszentrum L3S der Leibniz Universität, Hannover

[6] OFFIS Institute for Information Technology, Oldenburg

[7] Hochschule, Hannover

[8] IFL, Leibniz Universität, Hannover

来源：

ZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb | 2024年 / 119卷 / 05期

关键词：

Digital Twin; Information Exchange; Machine Learning; Manufacturing Network; Process Control; Retrofitting;

D O I：

10.1515/zwf-2024-1061

中图分类号：

学科分类号：

摘要：

The Future Lab Production demonstrates the potentials of digitalisation by using the die casting process as an example process. The project shows how manufacturing companies can digitalise their existing machines, analyse their data and exchange information along the supply chain while maintaining data sovereignty. The aim is to support companies with digitalisation from the machine to data platforms. The article describes the methods used, the concepts developed and their benefits. © 2024 Walter de Gruyter GmbH, Berlin/Boston, Germany.

引用

页码：372 / 377

页数：5

共 17 条

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[4] Kallisch J., Wunck C., Using Vertical Federated Learning in Industrial Supply Chains, Decision Science Institute
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[8] Lorenz A., Analyse des Laserstrahlabtragens für Den Wirtschaftlichen Einsatz im Werkzeug- Und Formenbau, (2009)
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[10] Denkena B., Dittrich M.-A., Lindauer M., Mainka J., Sturenburg L., Using AutoML to Optimize Shape Error Prediction in Milling Processes, Proceedings of the Machining Innovations Conference (MIC), (2020)

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