Today, the manufacturing industry faces numerous, often completely new challenges. Globalisation and digitalisation have long been responsible for increases in international competition and price pressure. Today, the demand for customised products with ever smaller batch sizes requires an increasing diversification of product portfolios, which in some cases has led to widely fluctuating production levels. Furthermore, there are more stringent demands on product quality, as well as calls for greater energy and resource efficiency. Moreover, energy and raw material prices are subject to strong fluctuations.
We want to help our customers and partners overcome these new challenges, especially those resulting from digitalisation. Together with you, we develop customised solutions to optimise production processes that are based on the right combination of physical and data-driven mathematical models (digital twin). Our aim is to systematically use all available information (process knowledge, data, models and measurements) to improve efficiency, reduce waste, and save resources. Furthermore, using our models we can identify and possibly even prevent errors early on, as well as increase flexibility and improve interactions between man and machine.
A holistic analysis, together with the development and implementation of tailored algorithms with real-time capability help us greatly in overcoming these challenges. By using these, it is possible to significantly improve, for instance, process automation, general time management, and product sequence optimisation.