In November 2019, the SeDiPeT Secure Digital Performance Twin network came up with the idea of developing the SI-CM3S Secure Industrial Condition Monitoring project, an innovative system that uses condition monitoring to reduce machine downtime in production.
The project consortium was formed by two companies, Schindler & Schill GmbH and SYSTEMA GmbH, as well as two research institutions, TH Deggendorf and TU Munich.
The application was approved in the ZIM program, the project duration was from 01.01.2021 to 30.09.2024. By initiating and supporting such projects, the Cluster Mobility & Logistics is able to shape the innovation field of logistics in a sustainable way.
In close cooperation with the Technical University of Munich, SYSTEMA has developed a pioneering method for monitoring and optimizing highly automated semiconductor production processes.
As part of this collaboration, a solution was developed that uses advanced data analysis and artificial intelligence (AI) to monitor and improve the efficiency and quality of production facilities in real time.
THD also worked on another aspect of data analysis on edge devices. Here, approaches were developed to execute trained machine learning models closer to the data source (on the edge). This reduces data rates and significantly increases system efficiency.
Partners
- TU München
- TH Deggendorf
- Schindler & Schill GmbH
- SYSTEMA GmbH