Digitalization & Automation
The research group “Digitalization and Automation“ attempts to close the gap between existing high-tech fluid power components as well as systems and modern information technology.
The challenge of digitalization within fluid technology lies in the implementation of concepts for increasing
- the added value of new components
- the efficiency of digital systems and
- the robustness of modern fluid mechatronics.
The fourth industrial revolution should be referred to as ongoing evolution, whose main feature is the global interconnection of intelligent components and systems. This endeavor has enormous potential and provides new research questions that need to be answered.
The development is not only visible in individual industries, it spreads across the entire industry and connects different components, systems and technologies. While solutions have been sought so far for the implementation of condition monitoring and predictive maintenance, holistic digitalization in fluid technology must now be expanded.
This assumes that basic functional patterns and design guidelines are reconsidered. Fluid mechatronic systems must be
- self-descriptive and
Here, the concepts of function definitions and asset administration shells are usefull.
Finally, advanced control algorithms and data analysis techniques using dynamic and nearly unbounded computational power, e.g. via cloud systems or high-performance computers, lead to unforeseen functionalities.
The research group focuses on the interface between fluid mechatronic systems and modern data processing. This wide-ranging topic is subdivided into sub-research areas.
Distributed Systems & Services in IIoT
The trend towards decentralized data processing is clearly visible. Where once central computers organized the control and analysis of processes, today you will find inexpensive embedded devices to fulfill the identical task. However, for the successful implementation of this new IIoT, the question of how the components communicate with each other needs to be discussed to ensure safe and robust operation.
Condition Monitoring & Predictive Maintenance
Systems have been developed for a long time that can describe the state of the system. New challenges exist in the automated analysis of this data in order to be able to generate knowledge in a targeted manner. The development of needs-based maintenance represents a possible application of this process.
Intelligent control algorithms
Control technology has long been a fundamental component of fluid power systems. New digitalization aspects enable the improvement and further development of these simple controller structures by incorporating precise sensor technology and embedded systems. Through innovative systems (for example, supported by machine learning) fundamentally new functionality can be achieved and the degree of automation can be increased.
Extended data analysis
A central element in the field of digitalization is data. Whether data is stored locally, processed and transformed into higher knowledge, or whether this should happen in large cloud-based networks is a key issue in the field of information technology. Helping to establish this process in fluid technology is an essential task, so as not to lose touch with other industries and specialist domains.
Along the industrial value chain of components and systems, data are generated that are of interest to all involved process participants. Although this information exists, it is often distributed and unstructured. Today, holistic systems are developed that enable consistent engineering, making the development process more efficient and economical.
These research areas will ultimately create new functionalities of components and systems and enable the development of new business areas tailored to the individual needs of customers.
Current Research Projects
Completed Research Projects
|Survey Industry 4.0 – Survey of Industry 4.0 in the domain of fluid power by the example of automated commissioning|
|ProMaschinenDaten – Availability Improvement of Construction Vehicles based on Global Machine Data Analysis|