The combination of physical machines and a suitable simulation environment enables the demonstration and evaluation of various applications and new technologies. This includes in particular the evaluation and demonstration of distributed production control systems and optimizations, which are researched in the group.
The goals of the group are the development of decentralized MES (Manufacturing Execution Systems) and the maintenance of the TIPI Lab to test them in realistic scenarios. A close cooperation with the group DCC enables the use of new highly efficient and high-performance embedded systems, which also enable sophisticated algorithms.
The so-called testbed-as-a-service approach of the TIPI Lab promotes cooperation with partners in research projects as well as in academic and vocational training.
The scientific questions of the MOM group are manifold and include, for example, the evaluation of robustness and flexibility of production processes, the efficiency of distributed control systems and the optimization of production through the use of intelligent self-organizing machines. A particular focus is on questions of information retrieval from manufacturing and suitable development processes for technical MOM platforms. Ultimately, this results in comprehensive IT support for new service-based ecosystems (platform economy, servitization) in manufacturing.
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Publications
2024
Challenges and Opportunities of Supply Chain - Development Methodologies for Big Data Analytics Systems - Plan-driven, Agile, Hybrid, Lightweight Approaches
Kallisch, Jonas; Wunck, Christoph; Marx-Gomez, Jorge; 2024
Datensparsamer Informationsaustausch innerhalb von Wertschöpfungsnetzwerken : ein Überblick über bestehende Systeme und Konzepte
Kallisch, J. and Runge, Maxim and Wunck, C. and Niemann, Karl-Heinz; Tagungsband AALE 2024 : 20. AALE-Konferenz. Bielefeld, 06.03.-08.03.2024; 2024
Sensorik und Automation: Schriften des Forschungsinstituts ISA 2024
Bartels, Thomas and Beyki, Mohammed and Flemming, Jesko and Grude, Leon and Homann, Hanno and Homeyer, Kai and Jakoblew, Sascha and Kallisch, Jonas and Kizilarslan, Metin and Knop, Werner and Lachmayer, Roland and Niemann, Karl-Heinz and Passoke, Jens and Patzke, Robert and Pawlak, Justus and Raabe, Jessica and Raveendran, Gurubaran and Renz, Franz and Schomburg, Helen and Sahan, Benjamin and Streitenberger, Martin and Tegeler, Sebastian and Will, Jens-Christian and Winnefeld, Jannis and Witte, Pascal and Wittig, Christoph and Wicht, Bernhard and Wulfmeier, Kirsten and Wunck, Christoph and Heüveldop, Dörte and Grotjahn, Martin; 2024
Zukunftslabor Produktion: Vernetzung, Modellierung und Optimierung in der industriellen Produktion
Kallisch, Jonas and Denkena, Berend and Kramer, Kathrin and Stürenburg, Lukas and Pachandrin, Slava and Rokicki, Markus and Walter, Jörg and Nein, Marcus and Voss, Marvin and Wunck, Christoph and Niemann, Karl-Heinz and Schmidt, Matthias and Dilger, Klaus and Niederée, Claudia and Hoffmann, Norbert; Zeitschrift für wirtschaftlichen Fabrikbetrieb; April / 2024
2023
Development Methodologies for Big Data Analytics Systems - Plan-driven, Agile, Hybrid, Lightweight Approaches
Kallisch, Jonas; Wunck, Christoph; Marx Gomez, Jorge ; 2023
Development of a Prototype for a Process Support and Analysis Platform for Small and Medium-sized Enterprises
Jonas KallischChristoph Wunck; International Journal of Computers and Their Applications; 07 / 2023
Green IT for I4.0 - Energieeffiziente und leistungsfähige IT-Architekturen für digitalisierte Produktionslinien
Dr. Frank Oppenheimer, Patrick Knocke; 11 / 2023
Mittelstand 4.0-Kompetenzzentrum Bremen
Daniel Schneider, Janina Kovacs, Stefan Wiesner, Markus Knak, Michael Teucke, Alexandra Pehlken, Patrick Knocke, Sven MattheisFlorian Borgwardt, Quynh Duong Phuong; September / 2023
Nachhaltigkeit durch Digitalisierung im Mittelstand - Chancen der Digitalisierung zur Erhöhung der Nachhaltigkeit in KMU-Anwendungsfällen – Ein Praxisbeitrag
H. Ekwaro-Osire, S. Wiesner, D. Bode, A. Pehlken ; Industrie 4.0 Management; Februar / 2023
Using vertical Federated Learning in industrial Supply Chains
Jonas KallischChristoph Wunck; Decision Science Institute; 11 / 2023
