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Is part of the Bibliography
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Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
(2017)
Towards inclusion of the freight rail system in the industrial internet of things - Wagon 4.0
(2017)
Eigene positive Erfahrungen mit Onlinekursen sowie die geringen Studierendenzahlen in der Präsenzlehre gaben den Anstoß zu einem Experiment mit einem offenen Onlinekurs auf der Plattform Udemy. Die Erfahrungen sowohl bei der Erstellung und als auch im Lehrbetrieb waren positiv und führten zu einer neuen Beschäftigung mit Inhalten und Lernenden, getrieben durch die Anforderungen der Lernplattform.
In the future, we expect manufacturing companies to follow a new paradigm that mandates more automation and autonomy in production processes. Such smart factories will offer a variety of production technologies as services that can be combined ad hoc to produce a large number of different product types and variants cost-effectively even in small lot sizes. This is enabled by cyber-physical systems that feature flexible automated planning methods for production scheduling, execution control, and in-factory logistics.
During development, testbeds are required to determine the applicability of integrated systems in such scenarios. Furthermore, benchmarks are needed to quantify and compare system performance in these industry-inspired scenarios at a comprehensible and manageable size which is, at the same time, complex enough to yield meaningful results.
In this chapter, based on our experience in the RoboCup Logistics League (RCLL) as a specific example, we derive a generic blueprint for how a holistic benchmark can be developed, which combines a specific scenario with a set of key performance indicators as metrics to evaluate the overall integrated system and its components.