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Features of Event-Driven Message Queuing Architectures in Manufacturing: A Reference Model for Comparison

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Gesellschaft für Informatik e.V.


With increasing digitization and the use of cost-effective, ever more intelligent sensor and actuator systems at the edges of classic IT networks (edge computing), ever-increasing amounts of data are continuously being generated and sent from a wide variety of data sources. At the same time, manufacturing processes are subject to dynamic adjustments such as staff shortages, material shortages and fluctuations in energy costs. In addition, there is the requirement to demonstrate the sustainability of produced goods within the supply chain and to the outside world, which requires the collection of key figures across all levels of the manufacturing pyramid – and ideally also across the entire life cycle of the product. What they all have in common is that a very large amount of continuously and simultaneously operating systems can process sent data quickly and can react to relevant events in near real time. To build these systems, increasingly distributed applications based on the principle of message queuing (MQ) and event handling are attracting increasing interest in the manufacturing industry. In this paper4, we surveyed recent models and architectures for such event-driven systems. Based on this survey, we propose a consolidated feature model to uniformly describe and evaluate event-driven manufacturing systems, regardless of whether an organization’s own architectural needs or the offers of external providers are evaluated.


Gudenkauf, Stefan; Franke, Javier; Behrens, Janek (2023): Features of Event-Driven Message Queuing Architectures in Manufacturing: A Reference Model for Comparison. INFORMATIK 2023 - Designing Futures: Zukünfte gestalten. DOI: 10.18420/inf2023_149. Bonn: Gesellschaft für Informatik e.V.. PISSN: 1617-5468. ISBN: 978-3-88579-731-9. pp. 1435-1451. Ökologische Nachhaltigkeit - Zukunft nachhaltig gestalten durch digitalisierte Wertschöpfungsprozesse (DigiWe). Berlin. 26.-29. September 2023