Fraunhofer Institute for Electronic Microsystems and Solid State Technologies EMFTThe DigiSeal research project is setting new standards in the predictive maintenance of mechanical seals, which are essential for many branches of industry. By using informed AI and the expertise of Fraunhofer EMFT, precise models are being developed that not only predict maintenance requirements, but also provide specific recommendations for action. Together with partners such as EagleBurgmann Germany GmbH & Co. KG, Molkerei Alois Müller GmbH & Co. KG and Munich University of Applied Sciences, digitalization in the industry is being driven forward and a significant contribution is being made to Industry 4.0.
Project DigiSeal: Predictive maintenance through informed AI
Industrial machines
DigiSeal project
The DigiSeal research project represents a significant advance in predictive maintenance, particularly for mechanical seals, which are a key component in numerous industrial applications. These seals are essential for the smooth operation of machines and systems by preventing the leakage of liquids or gases and thus helping to prevent machine failures. By using predictive maintenance, the service life of these seals can be maximized, unforeseen failures minimized and operational safety increased.
The DigiSeal project relies on the use of 'informed AI', a special form of artificial intelligence that is enriched not only with pure operating data, but also with domain-specific knowledge and empirical values. This informed AI makes it possible to make more precise and reliable predictions about the condition of mechanical seals by recognizing patterns and anomalies in the data at an early stage. This allows potential faults to be identified and maintenance measures to be initiated in good time before expensive and time-consuming failures occur.
Fraunhofer EMFT brings to this project its extensive expertise in the development of AI models based on anomaly detection and predictive maintenance. The models developed at Fraunhofer EMFT use both historical and real-time data to continuously monitor the condition of the mechanical seals. This not only detects deviations from the normal condition, but also generates recommendations for specific maintenance measures. These recommendations are based on in-depth model inference and provide operators with clear instructions that improve both the efficiency and safety of the systems.
Our partners in the project
A key advantage of the DigiSeal project is the close cooperation with leading industrial partners such as EagleBurgmann Germany GmbH & Co. KG, a global market leader in the field of industrial seals, and Molkerei Alois Müller GmbH & Co. KG, one of the leading food manufacturers in Germany. The involvement of Munich University of Applied Sciences also ensures that the latest scientific findings and innovative technologies flow directly into the development process.
By combining industrial know-how, scientific research and advanced AI technology, the DigiSeal project makes an important contribution to the digitalization and optimization of industrial processes within the framework of Industry 4.0. The project aims to take predictive maintenance to a new level by improving the efficiency and safety of production processes while reducing operating costs. The focus is on practical implementation to ensure that the solutions developed can be applied directly in industry and used in the long term.
The project is funded by the Bavarian Joint Research Programme (BayVFP) of the Free State of Bavaria - funding line “Digitalization” under the identification number DIK0559/04.