Quality assurance thanks to Machine Learning

A researcher, on the left, standing, explains something on the screen to a researcher, on the right, sitting.
By combining visual analytics and machine learning, VRVis helped a glassware manufacturer automate quality control, he said.

We approached the challenge of putting the quality assurance of an Austrian manufacturer of glass articles on a new AI footing with the clear goal of optimization. In this joint project, methods from the fields of visual analytics and machine learning were researched and adapted in order to automate quality control and assurance in the production of glass articles. Now even the smallest damages or imperfections can be detected automatically without any problems.

Visual exploration of Big Data

A group of researchers sits and stands in front of an desktop computer. You can see various colourful data visualizations on the computer screen.
The analysis of complex and big data can be improved greatly by data visualizations.

The visual computing platform TSM Visuals, developed together with our company partner HAKOM Time Series GmbH and data scientists from the energy industry, opens up brand new possibilities for exploration, interpretation, and evaluation of large and heterogeneous data using simultaneous interactive visualizations. Such an analysis provides trustworthy results in the quality assessment of data and guarantees better quality assurance of complex processes.

Predictive modelling

Visual Analytics Dashboards für die Energiewirtschaft
Predictive modeling uses data mining and probability to predict outcomes.

Data science and visual analytics offer the possibility of forecasting future results by means of different display types and predictive modelling based on real data. In our research project En2VA, we further developed an existing analysis platform into a potent communication tool for joint workshops of data scientists and experts, and optimized the processing of extremely large data volumes with millions of entries. This makes En2VA the ideal visual analytics solution for industry 4.0, for instance in the area of simulation-based product development, which allows for both the testing of data quality and the creation of forecast models and their evaluation in a quick and easily understandable way.

Data Science for Neuroscience

A researcher points with a pen to a screen where a brain data platform can be seen.
The VRVis researches and develops data-driven solutions for neuroscience.

Advanced mathematical methods, e.g. from the field of Machine Learning, are helpful tools in neuroscience, in particular to better understand the highly complex information processing of the brain. Our software framework Brain* offers web-based solutions for management, visualization, automatic information extraction as well as semantic and image-based search in very large collections of spatial image and network data. The unique selling proposition of our infrastructure are high-performance spatial data structures that allow searching the contents of tens of thousands of 3D image data and very large, dense network data in milliseconds.

Data Science for Industry 4.0 and 5.0

Three people are standing in front of a laptop in a factory environment.
Data analysis tools optimized visually and graphically for human perception are the decisive key element that strengthens users' confidence in computer-aided data science and decision-making processes.

As a key technology in the field of industrial production, visual analytics enables us to see through the data surrounding the production process through visual data analysis. In this context, the stability and scalability of visual analytics tools are crucial factors for their acceptance as reliable tools in Industry 4.0, such as in our INGRESS project. Our analytics solutions are characterized by their ability to handle complex data, as well as to perform pattern search and anomaly detection quickly and reliably. In the EDIH AI5production project we support companies in their digital transformation with know-how about human-centered AI and data science solutions.

Data Science of climate data

The back of a man and the back of a woman's head looking at a visualization depicting various heat zones of a city in shades of red.
Climate data, especially in urban areas, is above all very large, very varied - and highly complex. Visual analytics creates an ideal basis for experts to visually bring together this data and thus help make cities fit for the climatic changes of the future. (c) PID / David Bohmann

The role of visual analytics in the analysis of climate and weather data will be an even greater one in the future, as it is the only way to capture the complex interrelationships in their entirety and use them for better climate change adaptation solutions. VRVis has several experts specialized in climate and environmental data, for example working with Typical Meterological Year (TMY) time series or developing visual cockpits for biosolar technology performance assessment.