@inproceedings{BraunChengLaietal.2019, author = {Braun, Sebastian and Cheng, Chi-Tsun and Lai, Chow Yin and Wollert, J{\"o}rg}, title = {Microservice Architecture for Automation - Realization by the example of a model-factory's manufacturing execution system}, series = {Proceedings of the 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, booktitle = {Proceedings of the 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, pages = {33 -- 37}, year = {2019}, language = {en} } @inproceedings{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Simulation und Verifikation komplexer Handarbeitsprozesse durch die Kombination von Virtual Reality und Augmented Reality im Single-Piece-Workflow}, series = {Tagungsband: AALE 2020}, booktitle = {Tagungsband: AALE 2020}, isbn = {978-3-8007-5180-8}, pages = {4 Seiten}, year = {2020}, language = {de} } @inproceedings{UlmerBraunChengetal.2021, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Adapting augmented reality systems to the users' needs using gamification and error solving methods}, series = {Procedia CIRP - 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0}, volume = {104}, booktitle = {Procedia CIRP - 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2021.11.024}, pages = {140 -- 145}, year = {2021}, abstract = {Animations of virtual items in AR support systems are typically predefined and lack interactions with dynamic physical environments. AR applications rarely consider users' preferences and do not provide customized spontaneous support under unknown situations. This research focuses on developing adaptive, error-tolerant AR systems based on directed acyclic graphs and error resolving strategies. Using this approach, users will have more freedom of choice during AR supported work, which leads to more efficient workflows. Error correction methods based on CAD models and predefined process data create individual support possibilities. The framework is implemented in the Industry 4.0 model factory at FH Aachen.}, language = {en} } @inproceedings{UlmerLaiChengetal.2019, author = {Ulmer, Jessica and Lai, Chow Yin and Cheng, Chi-Tsun and Wollert, J{\"o}rg}, title = {Integration von VR und AR in Produktlebenszyklen - Eine {\"U}bersicht {\"u}ber die Nutzung virtueller Technologien im industriellen Umfeld}, series = {Automation 2019}, booktitle = {Automation 2019}, pages = {1 -- 12}, year = {2019}, language = {de} } @inproceedings{UlmerBraunLaietal.2019, author = {Ulmer, Jessica and Braun, Sebastian and Lai, Chow Yin and Cheng, Chi-Tsun and Wollert, J{\"o}rg}, title = {Generic integration of VR and AR in product lifecycles based on CAD models}, series = {Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, booktitle = {Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, year = {2019}, language = {en} } @inproceedings{BraunChengDoweyetal.2020, author = {Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Survey on Security Concepts to Adapt Flexible Manufacturing and Operations Management based upon Multi-Agent Systems}, series = {2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Proceedings}, booktitle = {2020 IEEE 29th International Symposium on Industrial Electronics (ISIE), Proceedings}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1109/ISIE45063.2020.9152210}, pages = {5 Seiten}, year = {2020}, abstract = {The increasing digitalization brings new opportunities but also puts new challenges to modern industrial systems. Software agents are one of the key technologies towards self-optimizing factories and are currently used to address the needs of cyber-physical production systems (CPPS). However their interplay in industrial settings needs to be understood better.This paper focusses on securing a cloud infrastructure for multi-agent systems for industrial sites. An industrial site contains multiple production processes that need to communicate with each other and each physical resource is abstracted with a software agent. This volatile architecture needs to be managed and protected from manipulation. The proposed infrastructure presents a security concept for TCP/IP communication between agents, machines, and external networks. It is based on open-source software and tested on a three-node edge cloud controlling a model-plant.}, language = {en} } @article{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Human-Centered Gamification Framework for Manufacturing Systems}, series = {Procedia CIRP}, volume = {93}, journal = {Procedia CIRP}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2212-8271}, doi = {10.1016/j.procir.2020.04.076}, pages = {670 -- 675}, year = {2020}, abstract = {While bringing new opportunities, the Industry 4.0 movement also imposes new challenges to the manufacturing industry and all its stakeholders. In this competitive environment, a skilled and engaged workforce is a key to success. Gamification can generate valuable feedbacks for improving employees' engagement and performance. Currently, Gamification in workspaces focuses on computer-based assignments and training, while tasks that require manual labor are rarely considered. This research provides an overview of Enterprise Gamification approaches and evaluates the challenges. Based on that, a skill-based Gamification framework for manual tasks is proposed, and a case study in the Industry 4.0 model factory is shown.}, language = {en} } @article{UlmerBraunChengetal.2022, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Gamification of virtual reality assembly training: Effects of a combined point and level system on motivation and training results}, series = {International Journal of Human-Computer Studies}, volume = {165}, journal = {International Journal of Human-Computer Studies}, number = {Art. No. 102854}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1071-5819}, doi = {10.1016/j.ijhcs.2022.102854}, year = {2022}, abstract = {Virtual Reality (VR) offers novel possibilities for remote training regardless of the availability of the actual equipment, the presence of specialists, and the training locations. Research shows that training environments that adapt to users' preferences and performance can promote more effective learning. However, the observed results can hardly be traced back to specific adaptive measures but the whole new training approach. This study analyzes the effects of a combined point and leveling VR-based gamification system on assembly training targeting specific training outcomes and users' motivations. The Gamified-VR-Group with 26 subjects received the gamified training, and the Non-Gamified-VR-Group with 27 subjects received the alternative without gamified elements. Both groups conducted their VR training at least three times before assembling the actual structure. The study found that a level system that gradually increases the difficulty and error probability in VR can significantly lower real-world error rates, self-corrections, and support usages. According to our study, a high error occurrence at the highest training level reduced the Gamified-VR-Group's feeling of competence compared to the Non-Gamified-VR-Group, but at the same time also led to lower error probabilities in real-life. It is concluded that a level system with a variable task difficulty should be combined with carefully balanced positive and negative feedback messages. This way, better learning results, and an improved self-evaluation can be achieved while not causing significant impacts on the participants' feeling of competence.}, 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{UlmerBraunChengetal.2020, author = {Ulmer, Jessica and Braun, Sebastian and Cheng, Chi-Tsun and Dowey, Steve and Wollert, J{\"o}rg}, title = {Gamified Virtual Reality Training Environment for the Manufacturing Industry}, series = {Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika (ME)}, booktitle = {Proceedings of the 2020 19th International Conference on Mechatronics - Mechatronika (ME)}, publisher = {IEEE}, address = {New York, NY}, doi = {10.1109/ME49197.2020.9286661}, pages = {1 -- 6}, year = {2020}, abstract = {Industry 4.0 imposes many challenges for manufacturing companies and their employees. Innovative and effective training strategies are required to cope with fast-changing production environments and new manufacturing technologies. Virtual Reality (VR) offers new ways of on-the-job, on-demand, and off-premise training. A novel concept and evaluation system combining Gamification and VR practice for flexible assembly tasks is proposed in this paper and compared to existing works. It is based on directed acyclic graphs and a leveling system. The concept enables a learning speed which is adjustable to the users' pace and dynamics, while the evaluation system facilitates adaptive work sequences and allows employee-specific task fulfillment. The concept was implemented and analyzed in the Industry 4.0 model factory at FH Aachen for mechanical assembly jobs.}, language = {de} }