The BrAIN project will utilize the emerging technological concepts from the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and the Data Science domain in order to analyse and understand the interaction pattern among individual process steps in the manufacturing and production industry.
A sophisticated self-learning algorithm will be developed as a part of this project, enabling process experts to alter the parameters of the manufacturing processes within predefined tolerance limits. Changes in the production process parameters should culminate in a resource-efficient forging process with the highest quality products and the least amount of scrap and rework. The communication interfaces of the modern automation systems have the ability to interoperate with one another while most of the brownfield automation systems do not have provisions to interoperate with each other. Integration of such interoperable systems requires a middleware that can mediate among heterogeneous brownfield systems by performing tasks like data mapping and translating communication protocols and information semantics. Development of such kind of middleware tool entails manually creating multiple interfaces pertaining to individual communication technologies and vendor tools present in the system. Therefore, resolving the interoperability issue across brownfield systems at the shop floor level remains one of the major obstacles for developing a unified data access layer. The Self-learning AI systems designed within this project will interact with the said unified data access layer in order to build the data sets on real-time operations.
The primary goals of LIT Cyber-Physical Systems Lab in this project is to foster interoperability across heterogeneous brownfield systems, as well as automatic integration of brownfield devices and systems with advanced AI and Data Science tools. To achieve these objectives, a service-oriented architecture-inspired CPS framework will be created, which will not only cater to the specific requirements of the BrAIN project but will also tackle a wide range of generic integration challenges involving both brownfield and greenfield technologies. The unified data access layer, which will consist of a message bus system and technology adapters, will be a key feature of this framework. The message bus system will be in charge of delivering data from producers to relevant consumers, while technology adapters will serve as a bridge between connected devices and the message bus. Individual devices and sub-systems will be wrapped using virtual administration shells that will be utilized to control, configure, manage, or monitor the system. Apart from that, in order to harmonize the communication & data access mechanism, a common communication interface will be implemented within the administration shell.
LIT | CPS Lab
Cyber-Physical Systems for Engineering and Production
Johannes Kepler University Linz
Altenberger Straße 69
LIT Open Innovation Center, Ground Floor
Prof. Dr. Alois Zoitl
+43 732 2468 9480