Consistent Evolution of Type-Instance Hierarchies in Industrial Information Models of Digital Twins

Research Topic:

Digital Twins of industrial devices constantly change: manufacturers, integrators, operators, and standardization bodies add new properties, adjust value ranges, and modify structures. The problem: when a manufacturer updates the "blueprint" of a device type, hundreds of installed device instances must be synchronized accordingly. My dissertation develops a systematic framework that decomposes such changes into atomic steps and ensures that descriptions of types and instances remain consistent. The goal is a continuous information flow across the entire asset lifecycle (from engineering to decommissioning).

Impact/Potential for Industry:

The systematic categorization of changes in industrial information models enables coordinated multi-stakeholder workflows between manufacturers, integrators, and operators. Automated consistency checks reduce manual synchronization effort and prevent drift between reality and the Digital Twin. This shortens (re-)engineering cycles, increases data quality, and creates foundations for comprehensive lifecycle management of Digital Twins with continuously evolving information models.

Personal Motivation for the Research Topic:

Information models form the semantic foundation for the productive use of AI agents in autonomous engineering and production scenarios. Without automated update mechanisms, synchronization efforts emerge that cannot be managed manually. In the future, device manufacturers will not only deliver physical components but make essential contributions to the Digital Twin of the overall plant through standardized information models. I am motivated to create the formal foundations for this vision: consistent, automatically manageable information models as a prerequisite for scalable AI-supported engineering workflows.

Note on Thesis Topics:

If you are interested in a thesis, please feel free to contact me at any time. I typically have more topics available than are officially advertised.

Teaching

• Informations- und Automatisierungstechnik (ITAT)
• Forschungspraktikum (Ansprechpartner)

12/2023 - today
Research assistant at the Chair of Automation Technology (VSA) at the Institute of Control Systems (IRS)
with Prof. Dr.-Ing. Mike Barth at Karlsruhe Institute of Technology

03/2023 – 11/2023
Automation and software engineer at OPVengineering GmbH
Software development for the automation of specialized electric motor test benches

2018 - 2022
Master's degree (M.Sc.) in Electrical Engineering and Information Technology at KIT

• Specialization: Sensor Systems
• Master thesis at IRS and Fraunhofer IOSB on the topic “Investigation on the Measurement Accuracy of a Laser-Induced Damage Threshold Testbed in the Short-Wave Infrared”

2014 - 2018
Bachelor’s degree (B.Sc.) in Electrical Engineering and Information Technology at KIT Bachelor thesis at ITIV on the topic “Conception and evaluation of methods of pattern recognition in time series of dynamic systems in the automotive context”