About the lab

Since the introduction of the term "Mechatronics" before 30 years ago, it has been developed into a discipline of engineering sciences and also been well established both in science and industry. It deals with the interaction of mechanical, electronic and information technology components. The Chair of Mechatronics at UDE was founded in 1991 and hence it’s one of the oldest university-based Chairs for Mechatronics in Germany. A team of about 20 scientists, headed by Prof. Dr.-Ing. Dr. h.c. Dieter Schramm, is mainly working with applications in the mobility sector and cable driven robots.

Featured research (4)

With the convergence of information technology (IT) and operational technology (OT) in Industry 4.0, edge computing is increasingly relevant in the context of the Industrial Internet of Things (IIoT). While the use of simulation is already the state of the art in almost every engineering discipline, e.g., dynamic systems, plant engineering, and logistics, it is less common for edge computing. This work discusses different use cases concerning edge computing in IIoT that can profit from the use of OT simulation methods. In addition to enabling machine learning, the focus of this work is on the virtual commissioning of data stream processing systems. To evaluate the proposed approach, an exemplary application of the middleware layer, i.e., a multi-agent reinforcement learning system for intelligent edge resource allocation, is combined with a physical simulation model of an industrial plant. It confirms the feasibility of the proposed use of simulation for virtual commissioning of an industrial edge computing system using Hardware-in-the-Loop. In summary, edge computing in IIoT is highlighted as a new application area for existing simulation methods from the OT perspective. The benefits in IIoT are exemplified by various use cases for the logic or middleware layer using physical simulation of the target environment. The relevance for real-life IIoT systems is confirmed by an experimental evaluation, and limitations are pointed out.
For the automated generation of simulation environments in the context of inland waterways navigation, a toolchain for the reconstruction of roadside buildings is used for the first time in this field. It was first implemented and tested for the reconstruction of roadside buildings. The toolchain uses data of a stereo camera to automatically generate models of the surrounding objects. This contribution describes the major changes that have to be made to adapt the toolchain to the changed environment. An unmanned aerial vehicle (UAV) is used to take images of specific objects. Due to the limited space on this UAV, only the supplied camera is used. Thus, the further steps in the toolchain have to be adapted. For the evaluation of the resulting model quality images of two bridges are considered. The implemented programs Metashape and Meshroom are compared with each other in terms of quality and computational effort. It is shown that the resulting model quality is better by using the program Metashape. Regarding the computational effort, the necessary time as well as the CPU and GPU utilization are reviewed. Although the GPU utilization is similar, Metashape outperforms Meshroom in terms of CPU utilization and total processing time. Furthermore, two different image recording methods are compared. On the one hand, models are reconstructed from only the top view. On the other hand, a tilted viewing angle with images from both sides of the bridges is used.
A reliable and cost-effective transport system is essential for a highly developed economy. This is especially true for countries with its high population and industrial density. In this context, inland vessels are an efficient, climate-friendly and safe way of transporting goods. However, inland vessels are facing major challenges: The change in transport modalities towards containerized cargo in smaller batch sizes (freight structure effect) increasingly re-quires an adaptation of the fleet towards smaller, more flexible deployable ship units (Renner 2003, Winter 2014). The resulting additional demand for ship staff further aggravates the already existing shortage of qualified ship masters. In addition, the challenges posed by demographic change continue to exist. On the other hand, it can be observed that the competing modes of transport, road and rail, are driving the development towards automated driving and can gain a cost advantage over inland waterways due to the expected personnel savings.

Lab head

Dieter Hermann Schramm
Department
  • Abteilung Maschinenbau und Verfahrenstechnik

Members (27)

Tobias Bruckmann
  • University of Duisburg-Essen
Frédéric Etienne Kracht
  • DST - Development Centre for Ship Technology and Transport Systems
Niko Maas
  • University of Duisburg-Essen, Duisburg, Germany
Philipp Maximilian Sieberg
  • Schotte Automotive GmbH & Co. KG
Benjamin Hesse
  • University of Duisburg-Essen
Thomas Weber
  • University of Duisburg-Essen
Stephan Schweig
  • University of Duisburg-Essen
Roberto Bardini
Roberto Bardini
  • Not confirmed yet
Peter Lukas Peters
Peter Lukas Peters
  • Not confirmed yet
Sebastian Lefèvre
Sebastian Lefèvre
  • Not confirmed yet
Sascha Türke
Sascha Türke
  • Not confirmed yet
H. Braeuchle
H. Braeuchle
  • Not confirmed yet
Sebastian Wagner
Sebastian Wagner
  • Not confirmed yet
Roland Boumann
Roland Boumann
  • Not confirmed yet
Patrik Lemmen
Patrik Lemmen
  • Not confirmed yet

Alumni (16)

N.K. Khamis
  • National University of Malaysia
Lars Mikelsons
  • University of Augsburg
Rudi Kurniawan
  • Syiah Kuala University
Yat Sheng Kong
  • APM Engineering & Research