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 measurement technology and data analysis enables us to provide efficient and precise solutions for challenges in statistics, sensor technology, and physical modeling. Our multidisciplinary approach allows us to think outside the box and thus generate added value.
Offer
Modeling & Simulation
The project group Modeling & Simulation is concerned with the mathematical-physical simulation of models. The focus is on the scientific aspect, i.e., investigating mathematical models, including partial differential equations and ordinary differential equations.
In cooperation with the customer, we model physical systems and support our customers to understand them better. Modeling a system can also help reduce prototyping costs, show potential in the design, and assist in troubleshooting.
Measurement & Sensoric
The Measurement Technology & Sensor Technology team is concerned with designing sensor systems and measurement procedures. Thereby, physical knowledge serves to solve our customers’ challenges regarding physical properties and convert them into relevant digital data.
The team develops innovative solutions for optimization in manufacturing (Industry 4.0), innovative technologies such as Smart Key or Smart City, and data connectivity to achieve a networked future. We support our customers in digitizing their sensor systems and identifying possible sources of error in the measurement system.
Statistics & Data Analysis
The project team Statistics & Data Analysis goal is to develop knowledge and expertise in statistics, algorithms, and data analysis. Furthermore, best practices for data visualization will be created.
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 allows us to identify previously unknown relationships with the customer.
Predictive Maintenance
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 are data collection and preprocessing, statistics, machine learning, and modeling to find and validate use cases. However, implementing the found use cases in a production system is also adjacent.
Erik Hänel
Head of Analytics & Sensorics