TY  - CHAP
A1  - Ulmer, Jessica
A1  - Braun, Sebastian
A1  - Cheng, Chi-Tsun
A1  - Dowey, Steve
A1  - Wollert, Jörg
T1  - Adapting Augmented Reality Systems to the users’ needs using Gamification and error solving methods
T2  - Procedia CIRP
N2  - 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.
KW  - Augmented Reality
KW  - Adaptive Systems
KW  - Gamification
KW  - Error Recovery
Y1  - 2021
U6  - http://dx.doi.org/10.1016/j.procir.2021.11.024
SN  - 2212-8271
N1  - Part of special issue: 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0
VL  - 104
SP  - 140
EP  - 145
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Braun, Sebastian
A1  - Cheng, Chi-Tsun
A1  - Dowey, Steve
A1  - Wollert, Jörg
T1  - Performance evaluation of skill-based order-assignment in production environments with multi-agent systems
JF  - IEEE Journal of Emerging and Selected Topics in Industrial Electronics
N2  - 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.
KW  - cyber-physical production systems
KW  - event-based simulation
KW  - multi-agent systems
KW  - digital factory
KW  - industrial agents
Y1  - 2021
U6  - http://dx.doi.org/10.1109/JESTIE.2021.3108524
SN  - 2687-9735
IS  - Early Access
PB  - IEEE
CY  - New York
ER  -