Analytics & Sensorics

The entire process of scientific knowledge acquisition is covered by the Center of Excellence Analytics & Sensorics. It is divided into the four subject areas of measurement technology & sensorics, predictive maintenance, modeling & simulation and statistics & data analysis. It can therefore be placed chronologically between basic research and prototype development

Our profound knowledge in the field of measurement technology and data analysis enables us to provide efficient and precise solutions for challenges in the fields of statistics, sensor technology and physical modeling. Our multidisciplinary approach allows us to think outside the box and thus generate added value.

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Eric Hänel

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Erik Hänel


Modelling & Simulation

The project group Modeling & Simulation is concerned with the mathematical-physical simulation of models. The focus is on the scientific aspect, i.e. the investigation of mathematical models, which include, among others: partial differential equations and ordinary differential equations.

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

Measurement & Sensoric

The Measurement Technology & Sensor Technology team is concerned with the design of sensor systems and measurement procedures. Thereby physical knowledge serves as a way to solve our customers’ challenges regarding physical properties and to convert them into relevant digital data.

The team develops innovative solutions for optimization in manufacturing (Industry 4.0), smart technologies such as Smart Key or Smart City as well as data connectivity to achieve a networked future. We support our customers in digitizing their sensor systems and in identifying possible sources of error in the measurement system.

Statistics & Data Analysis

The goal of the project team Statistics & Data Analysis is to develop knowledge and expertise in the fields of statistics, algorithms and data analysis. Furthermore, best practices for data visualization will be developed.

Internally we work as a think tank for statistics and data analysis. We enable our clients to better understand themselves by analyzing their data and extracting hidden information. An in-depth parameter analysis enables us to identify relationships that were previously unknown to the customer.

Predictive Maintenance

The working group Predictive Maintenance is concerned with the condition monitoring of production machines and, based on this, the prediction of damage events. This is intended to increase reliability, improve maintenance planning and save costs. In addition, transparent condition monitoring allows better control of production. The main tasks here are data collection and preprocessing, statistics, machine learning and modelling to find and validate use cases. However, the implementation of the found use cases in a production system is also adjacent.