During his PhD studies, Christian Remi Wewer researched the integration of digital twins and machine learning models for optimizing industrial drying processes. Christian Remi Wewer's research addresses major challenges in the field, such as data scarcity and the complexity of implementing machine learning models in factory environments. The project was conducted in close collaboration with C.C. Jensen A/S, a manufacturing company located in South Funen.

The research findings contribute to the optimization of drying processes both broadly and specifically within C.C. Jensen. Furthermore, the methods and software developed during the project can be generally applied to other processes with similar data modalities.

The PhD study was completed at Department of Electrical and Computer Engineering (ECE), Faculty of Technical Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Friday, 20 September 2024 at 13:00
Place: Building 5123, room 314, Aarhus University, Helsingforsgade 10, 8200 Aarhus N
Title of PhD thesis: Improving Filter Insert Performance and Quality using Data Analytics
Contact information: Christian Remi Wewer, e-mail: chw@ece.au.dk
Members of the assessment committee:
Professor Mikkel Baun Kjærgaard, Mærsk Mc-Kinney Møller Instituttet, SDU, Denmark
Professor Franco Zambonelli, Dipartimento di Scienze e Metodi dell'Ingegneria, University of Modena and Reggio Emilia, Italy
Associate Professor Stefan Hallerstede (chair), Department of Electrical and Computer Engineering (ECE), Aarhus Universitet, Denmark
Main supervisor:
Professor Peter Gorm Larsen, Department of Electrical and Computer Engineering, Aarhus University, Denmark
Co-supervisor:
Associate Professor Lukas Esterle, Department of Electrical and Computer Engineering, Aarhus University, Denmark
Language: The PhD dissertation will be defended in English

The defence is public.
The PhD thesis is available for reading at the Graduate School of Technical Sciences/GSTS, Ny Munkegade 120, building 1521, 8000 Aarhus C.