QuickCheck profiles

Are you considering applying for a QuickCheck, but don't yet know specifically what it involves? To give you an insight into what we offer, we publish QuickChecks that have already been carried out in profiles on this page. Here you can read about the approaches we take to your questions and the results QuickChecks can lead to.


Automated anomaly detection

Siempelkamp NIS Ingenieurgesellschaft mbH provides monitoring solutions for large steam and gas turbine generator sets in the energy industry. For these plants, a monitoring concept has already been developed. The goal of the QuickCheck is to investigate the extent to which an AI/ML solution can be developed to automatically distinguish normal machine plant behavior from abnormal behavior.


Condition-oriented analysis of pipelines

The condition of underground infrastructure systems can be analyzed in several ways. Direct inspections by using robots are state of the art  but those approaches are epxensive and time consuming. Meanwhile, network operators have more or less extensive damage statistics and inspection findings. To support operators, the company 3S Consult carries out age-dependent analyses of the pipeline condition. The QuickCheck examines the extent to which an AI can assist experts in this process.


Hardware-accelerated SoC platforms

PLC2 is an authorized training partner for FPGA technologies from Xilinx Inc. as well as for SoC/MPSoC architectures and offers customized solutions and hardware accelerators. The combination with extensive expertise in imagingADAS systems for automated driving and data logging, makes PLC2 an outstanding industry partner for developments in the automotive image processing area on real-time capable hardware structures.


Simulation models in AI systems engineering

Knowtion GmbH is a data science company with expertise in research, development and application of data processing algorithms, e.g. for sensor or machine data. For automated driving, complex virtual development and test environments are already used, e.g. to generate vehicle or traffic scenario data, but also sensor data virtually. The goal is to train or test AI-based algorithms for environment perception at an early stage in virtual driving tests with corresponding sensor models.  


Energy consumption optimization during One-Pedal-Driving

The ARADEX AG develops electrical powertrain solutions for commercial and utility vehicles, construction machinery and marine applications. Besides these innovative hardware solutions ARADEX offers software services, which shall be augmented with AI technology. Data shall be analyzed e.g., to improve the available range of the electric vehicle or to identify malicious driving behavior in regards to battery life.


Plant monitoring for grinding machines

Vollmer Werke Maschinenfabrik GmbH is a SME mechanical engineering company and one of the leading manufacturers of machines for processing rotary tools, circular saws and metal-cutting band saws. The company's portfolio includes around 60 types of grinding machines, which generate a varying amount of measurement data per grinding process, depending on the sensor equipment. Currently, this data is evaluated manually and, if necessary, by process experts.


Optimized production of UHCP building materials

Hypercon Solutions UG is developing a plant concept for the automated production of UHCP building materials (ultra-high-performance concrete). In the individual automated plants, sensors collect and process data during the production process. The collected data from all plants will be used in the future to develop solutions with AI methods (artificial neural networks, ANN) that optimize the UHPC recipes used and/or the production process in terms of quality and cost-effectiveness, among other things.