@inproceedings{UlmerMostafaWollert2022,
  author    = {Ulmer, Jessica and Mostafa, Youssef and Wollert, J{\"o}rg},
  title     = {Digital Twin Academy: From Zero to Hero through individual learning experiences},
  series = {Tagungsband AALE 2022 / Herausgegeben von der Hochschule f{\"u}r Technik, Wirtschaft und Kultur Leipzig},
  booktitle = {Tagungsband AALE 2022 / Herausgegeben von der Hochschule f{\"u}r Technik, Wirtschaft und Kultur Leipzig},
  isbn      = {978-3-910103-00-9},
  doi       = {10.33968/2022.33},
  url       = {http://nbn-resolving.de/urn:nbn:de:bsz:l189-qucosa2-776097},
  pages     = {1 -- 9},
  year      = {2022},
  abstract  = {Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.},
  language  = {en}
}
@article{UlmerBraunChengetal.2023,
  author    = {Ulmer, Jessica and Braun, Carsten and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg},
  title     = {A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation},
  series = {International Journal of Production Research},
  journal   = {International Journal of Production Research},
  publisher = {Taylor \& Francis},
  issn      = {0020-7543 (Print)},
  doi       = {10.1080/00207543.2023.2166140},
  year      = {2023},
  abstract  = {Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers' cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.},
  language  = {en}
}