Michelle Jungmann

• Master of Science
• Karlsruhe Institute of Technology

Extracting Digital Twin models by fusing expert knowledge with Internet of Things data remains a challenging and open research area. Existing literature offers very limited approaches for seamless and systematic extraction of Digital Twin models from these combined sources. In this paper, we address the research gap by proposing a novel approach th...

Integrating expert knowledge in data-driven Digital Twins can lead to better-informed underlying models. Achieving systematic integration, however, remains a complex challenge. In this study, we propose an initial approach for hybrid model extraction by systematically fusing expert knowledge statements with Internet of Things data from manufacturin...

Data-driven Digital Twin approaches have gained popularity in research literature, particularly in relation to Industry 4.0 achievements. Data-driven Digital Twins process widely available real-time data in an automated manner to extract models from various systems of interest. However, these model extraction approaches commonly lack systematic int...