New Terms, Simply Explained

Machine learning: A model is trained with known input data to generate predictions for new, unknown data points, and the model learns to recognize correlations and patterns in the input data.

Sequential learning: In an iterative (i.e., repetitive) process, a machine learning model is trained and used to predict unknown data. The most promising predictions are then tested. In the next sequential learning step, the model is then additionally trained using the test results from the previous iteration. This helps the model better understand relationships and patterns so that the model’s predictive power improves with each iteration.

Data Integration & Analytics Platform (DIAP): This platform developed by the DSAI team makes it possible to combine, analyze, and visualize data from all LANXESS systems as well as from a variety of external systems. Within the framework of projects in the production environment, the platform is used to improve processes, identify bottlenecks, predict maintenance requirements, increase production output, and improve overall efficiency.

Power BI: This term refers to a collection of software services, apps, and interfaces that make it possible to link, import, and visualize data from different sources. Power BI can be used to access reports not only locally on an individual PC, but also via a browser from anywhere in the world. Using Mobile Power BI apps, reports and dashboards can also be accessed via smartphones. This applies to Windows, iOS, and Android devices.