@inproceedings{ChavezBermudezCruzCastanonRuchayetal.2022,
  author    = {Chavez Bermudez, Victor Francisco and Cruz Castanon, Victor Fernando and Ruchay, Marco and Wollert, J{\"o}rg},
  title     = {Rapid prototyping framework for automation applications based on IO-Link},
  series = {Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkr{\"a}ftemangel},
  booktitle = {Tagungsband AALE 2022: Wissenstransfer im Spannungsfeld von Autonomisierung und Fachkr{\"a}ftemangel},
  editor    = {Leipzig, Hochschule f{\"u}r Technik, Wirtschaft und Kultur},
  address   = {Leipzig},
  isbn      = {978-3-910103-00-9},
  doi       = {10.33968/2022.28},
  pages     = {8 Seiten},
  year      = {2022},
  abstract  = {The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.},
  language  = {en}
}
@article{BraunChengDoweyetal.2021,
  author    = {Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {Performance evaluation of skill-based order-assignment in production environments with multi-agent systems},
  series = {IEEE Journal of Emerging and Selected Topics in Industrial Electronics},
  journal   = {IEEE Journal of Emerging and Selected Topics in Industrial Electronics},
  number    = {Early Access},
  publisher = {IEEE},
  address   = {New York},
  issn      = {2687-9735},
  doi       = {10.1109/JESTIE.2021.3108524},
  year      = {2021},
  abstract  = {The fourth industrial revolution introduces disruptive technologies to production environments. One of these technologies are multi-agent systems (MASs), where agents virtualize machines. However, the agent's actual performances in production environments can hardly be estimated as most research has been focusing on isolated projects and specific scenarios. We address this gap by implementing a highly connected and configurable reference model with quantifiable key performance indicators (KPIs) for production scheduling and routing in single-piece workflows. Furthermore, we propose an algorithm to optimize the search of extrema in highly connected distributed systems. The benefits, limits, and drawbacks of MASs and their performances are evaluated extensively by event-based simulations against the introduced model, which acts as a benchmark. Even though the performance of the proposed MAS is, on average, slightly lower than the reference system, the increased flexibility allows it to find new solutions and deliver improved factory-planning outcomes. Our MAS shows an emerging behavior by using flexible production techniques to correct errors and compensate for bottlenecks. This increased flexibility offers substantial improvement potential. The general model in this paper allows the transfer of the results to estimate real systems or other models.},
  language  = {en}
}
@inproceedings{AlhwarinFerreinGebhardtetal.2015,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Gebhardt, Andreas and Kallweit, Stephan and Scholl, Ingrid and Tedjasukmana, Osmond Sanjaya},
  title     = {Improving additive manufacturing by image processing and robotic milling},
  series = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden},
  booktitle = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden},
  doi       = {10.1109/CoASE.2015.7294217},
  pages     = {924 -- 929},
  year      = {2015},
  language  = {en}
}