@inproceedings{EvansBraunUlmeretal.2022,
  author    = {Evans, Benjamin and Braun, Sebastian and Ulmer, Jessica and Wollert, J{\"o}rg},
  title     = {AAS implementations - current problems and solutions},
  series = {20th International Conference on Mechatronics - Mechatronika (ME)},
  booktitle = {20th International Conference on Mechatronics - Mechatronika (ME)},
  publisher = {IEEE},
  isbn      = {978-1-6654-1040-3},
  doi       = {10.1109/ME54704.2022.9982933},
  pages     = {6 Seiten},
  year      = {2022},
  abstract  = {The fourth industrial revolution presents a multitude of challenges for industries, one of which being the increased flexibility required of manufacturing lines as a result of increased consumer demand for individualised products. One solution to tackle this challenge is the digital twin, more specifically the standardised model of a digital twin also known as the asset administration shell. The standardisation of an industry wide communications tool is a critical step in enabling inter-company operations. This paper discusses the current state of asset administration shells, the frameworks used to host them and their problems that need to be addressed. To tackle these issues, we propose an event-based server capable of drastically reducing response times between assets and asset administration shells and a multi-agent system used for the orchestration and deployment of the shells in the field.},
  language  = {en}
}
@incollection{NiemuellerLakemeyerReuteretal.2017,
  author    = {Niemueller, T. and Lakemeyer, G. and Reuter, S. and Jeschke, S. and Ferrein, Alexander},
  title     = {Benchmarking of Cyber-Physical Systems in Industrial Robotics: The RoboCup Logistics League as a CPS Benchmark Blueprint},
  series = {Cyber-Physical Systems: Foundations, Principles and Applications},
  booktitle = {Cyber-Physical Systems: Foundations, Principles and Applications},
  publisher = {Academic Press},
  address   = {London},
  doi       = {10.1016/B978-0-12-803801-7.00013-4},
  pages     = {193 -- 207},
  year      = {2017},
  abstract  = {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.},
  language  = {de}
}
@incollection{NiemuellerZwillingLakemeyeretal.2017,
  author    = {Niemueller, Tim and Zwilling, Frederik and Lakemeyer, Gerhard and L{\"o}bach, Matthias and Reuter, Sebastian and Jeschke, Sabina and Ferrein, Alexander},
  title     = {Cyber-Physical System Intelligence},
  series = {Industrial Internet of Things},
  booktitle = {Industrial Internet of Things},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-42559-7},
  doi       = {10.1007/978-3-319-42559-7_17},
  pages     = {447 -- 472},
  year      = {2017},
  abstract  = {Cyber-physical systems are ever more common in manufacturing industries. Increasing their autonomy has been declared an explicit goal, for example, as part of the Industry 4.0 vision. To achieve this system intelligence, principled and software-driven methods are required to analyze sensing data, make goal-directed decisions, and eventually execute and monitor chosen tasks. In this chapter, we present a number of knowledge-based approaches to these problems and case studies with in-depth evaluation results of several different implementations for groups of autonomous mobile robots performing in-house logistics in a smart factory. We focus on knowledge-based systems because besides providing expressive languages and capable reasoning techniques, they also allow for explaining how a particular sequence of actions came about, for example, in the case of a failure.},
  language  = {en}
}