Universities and research - some of our projects
Here you will find a brief insight into our projects with various universities:
At the Center for Wind Turbine Drives (CWD) and the Institute for Machine Elements (IMSE), Optimizer4D measuring systems are used to investigate the tribological behavior of rolling bearings in interaction with lubricants and imposed loads.
At the Machine Tool Laboratory, scientists are investigating the behavior of tools with defined and undefined cutting edges in the manufacturing process and use the Optimizer4D to derive findings on wear detection, the formation of grinding burns and hardness curves.
KIT Karlsruher Institut für Technologie
Together with the Institute for Production Technology (WBK), QASS is researching is jointly researching the use of structure-borne sound in the field of additive manufacturing.
To this end, QASS has integrated additional sensors in the form of photodiodes for the qualitative evaluation of the laser effect. The resulting raw data is used for machine learning methods to evaluate the formation of pores during a selective laser melting process..
Ruhr Universität Bochum
Together with RUB, we are developing solutions for the series production of solutions for monitoring green compacts and component quality. This involves transferring large amounts of process data to cloud storage and machine learning methods are developed together with RUB.
University of Southampton (UOS)
Together with the UOS, we have carried out major research projects the behavior of gearboxes in combination with lubricants and the accompanying electric fields. To do this, we connected sensors UOS and transmitted the raw data to UOS with extreme time resolution.
Frauenhofer Gesellschaft für Werkstoffmechanik (IWM)
As part of a larger joint project, QASS has integrated various sensor and data sources into its measuring systems. One aspect of the project is the calculation of resulting infrared spectra from theoretical reactions in the lubricant. This helps the risk assessment of large systems when the in-situ condition is compared with the target condition.
Industrial-grade in-line infrared spectrometers from Hydac can be used for this purpose.
At Kaiserslautern University of Applied Sciences, the application of the Barkhausen noise is being intensively investigated. Since 2016, QASS has included the method added the method to its portfolio as an additional sensor. The strongest benefits lie in the spectral data representation of the Barkhausen signal and the electronic electronic filters in combination with the Python application. This enables achieve reliable industrial stability.