Projects and products of the department MRD

Das Projekt CC-King hat sich zum Ziel gesetzt, KI-Spitzenforschung mit etablierten Ingenieurdisziplinen zu verbinden. Hierdurch sollen KI-Methoden und maschinelle Lernverfahren (ML) entsprechend den typischen Anforderungen und Vorgehensweisen von Ingenieuren nutzbar gemacht werden.

Multisensory system for AI-based drone detection and classification with situation visualization.

The Karlsruher Forschungsfabrik for AI-integrated production offers the special opportunity to research and develop the topic of “Intelligent Production” in a practical way on real processes.

“AutoInspect” is a system for continuous object assessment (in real time) by multimodal inspection along the production cycle. Both a direct reaction to the results and their long-term observation are possible. The system is supported by a digital quality twin with open I4.0 standards.

The dynOpt energy manager is primarily intended for commercial properties such as apartment buildings and neighbourhoods where several components such as heat pumps, PV systems, solar heating systems, gas boilers or CHP units are operated in a coupled manner. Furthermore, dynOpt-En monitors energy consumption and costs and compares the real values with the expected values. In this way, malfunctions can be detected promptly and signalled via a clear visualisation or reported to the operator.

For the early detection of health-threatening contaminations in drinking water, therefore, an online-capable broadband test procedure for drinking water conformity is needed that reacts very quickly and reliably, is robust against false alarms, can be operated by persons without scientific qualifications and whose acquisition and maintenance costs are economically justifiable. Currently, such online-capable and broadband sensor systems are not commercially available.

The production of bulk and fine chemicals on the basis of renewable raw materials has become increasingly important in recent years as "white biotechnology". Surfactants, which are currently produced industrially to a large extent from petrochemical starting materials, are a potential product for the use of biotechnological production processes.

In order to keep the total operating costs of wind turbines (WTGs) competitive, the risk of failure must be minimized, maintenance costs reduced, and system availability and energy efficiency increased. This goal is achieved by introducing the most efficient, automated multi-sensory online monitoring and diagnostic systems - so-called Condition Monitoring Systems (CMS) - whose economic importance is increasingly recognized by wind farm operators, manufacturers and insurers.

Process engineering processes usually have a large number of process variables which generate an alarm when a previously defined threshold value is exceeded in the event of abnormal process behavior. If a fault occurs in a central plant section, this leads to a flood of alarms, since the individual process variables are interdependent and the fault propagates through the plant.

By means of the developed and integrated data management and above all thanks to the advanced data evaluation, it is possible to carry out systematic data evaluation as well as plant monitoring, thus increasing the efficiency of the production process.