Analytics & Sensorics

“Using data science methods and background physics knowledge, we extract relevant information from measurements and simulations to ensure that your analyses generate real added value.”

Erik Hänel | Senior Consultant & Head of Analytics & Sensorics

Using data science methods and background physics knowledge, we extract relevant information from measurements and simulations to ensure that your analyses generate real added value.

Erik Hänel
Senior Consultant & Head of Analytics & Sensorics

Breakthrough cutting-edge technologies must be based on scientifically sound findings. This is precisely why CoE Analytics and Sensorics offers you a partner who will act at eye level with you. We stand by them in the realization of new technologies.

Competencies

We are happy to consult with you to develop the innovative design of your new products. Prototype development, simulations as well as our sensor technology research are part of our services. Use our know-how to make your product development as effective and efficient as possible.

We bring in-depth knowledge of Data Science methods and have a high level of physical expertise. This provides the optimal added value for your measurements and models. We are happy to support you and to discuss all technical issues with you.

Our talents deal with the simulation of mathematical models. The technical focus is on the scientific aspect, i.e. the mathematical study of partial and ordinary differential equations.

In cooperation with the customer, we model physical systems and help our customers to understand them better. Modeling a system can also help reduce prototype costs, highlight potentials in the design, and assist in troubleshooting.

In science-related programming, it is essential to represent the mathematical-physical models as accurately as possible. At the same time, it is desirable to keep runtimes within limits and to minimize rounding errors.

We combine tools for data analysis & Co. with the necessary scientific background, advanced algorithms and modern software development to create flexible applications for your requirements. C++, Python, MATLAB/Simulink and other frameworks are part of our extensive toolbox.

We support you in the design of individual sensor systems as well as entire measurement concepts. In particular, we are familiar with the most advanced and precise measurement methods in modern industry. For any challenge with physical properties, we are happy to support you with innovative approaches.

If you are looking for support in connecting your measuring instruments to a production system via e.g. MQTT or OPC UA, we are also the right partner for you. Together with our other areas of expertise, we will create the perfect solution for you. With us, smart production is within reach.

Data is the gold of modern industry, especially when you use it to make key strategic decisions. We help you find the features in your data and facilitate their interpretation through modern visualizations and statistical analysis.

Data Science or Data Analytics are more than “just” Machine or Deep Learning. We focus on statistical methods that are not a black box, so you can always understand how an algorithm arrived at a result. If there is additionally a concrete added value to be expected from Machine Learning, this completes our methods.

Any type of automated analysis or maintenance requires constant monitoring of sensor data and real-time processing of that data. In most applications today, this sensor data consists of 2D data especially images.

Analytical image processing is the state-of-the-art in this field. Use our competences to advance automation in your industry. Join us in modernizing your products and services to meet the demands of today’s market.

Publications

Open Source Solutions

NumeRe: Framework für Numerische Rechnungen (GPLv3) – Scientific data analysis for Windows® redefined.

Fitting | Data analysis | Plotting | Matrix operations | FFT | Extensible Framework | Multiple file formats | Programmable | Open source | Free for everyone

Project References