DIGITbrain passes EC review with flying colours

The final accomplishments of the 42-month-long DIGITbrain project were presented during the EC review in Brussels. HUN-REN SZTAKI was among the main contributors who made this project a success that enabled Manufacturing-as-a-Service for several European SMEs.

DIGITbrain, the EU H2020 project that supported 21 cross-national application experiments with an integrated digital platform finished at the end of 2023. The notion of the project was to bring agility and innovation to manufacturing SMEs by empowering the network of Digital Innovation Hubs (DIHs) with an integrated digital platform that enables Manufacturing-as-a-Service (MaaS). 36 European organisations (manufacturing SMEs, universities, research institutes) joined forces to implement this ambitious project including Fraunhofer and DFKI from Germany. 

Digital twins enable customised industrial products to facilitate cost-effective distributed and localised production for manufacturing SMEs by leveraging edge-, cloud- and HPC-based modeling, simulation, optimisation, analytics, and machine learning tools. The experiments represented an immensely wide range of use cases from the manufacturing industry including agricultural robots, fabric production, automotive solutions, brewing process and parquet flooring just to list a few. The descriptions of the experiments can be found here.

In order to prepare for the review, DIGITbrain partners gathered for a last technical face-to-face meeting in sunny Budapest last autumn. HUN-REN SZTAKI hosted the two-day event, where the partners finalized the work schedule for the remaining months and discussed sustainability matters to ensure that by focusing on emphasizing the value of collective insights and shared expertise the legacy of DIGITbrain can live on.

Within the project, HUN-REN SZTAKI (Laboratory of Parallel and Distributed Systems) was responsible for the Data Work Package focusing on the Reference architectures for data management, data delivery, pre-processing and integration. These architectures can be deployed in the cloud or on the edge, on-demand, which are then orchestrated automatically by the DIGITbrain Platform. Complex data services can be constructed from a large set of ready-made data service building blocks for more challenging data integration, and data analytics tasks. Almost all the popular Machine Learning frameworks are offered for all the developers and end users of the platform as off-the-shelf toolboxes, which can easily be launched without IT expertise and used right away via a convenient graphical user interface, having a wide range of data connectivity options.

Reviewers in their evaluation report highlighted that despite the perturbances, unforeseen risks, and unexpected events that occurred in the project’s lifetime (starting with COVID-19), the achieved results are convincing, impressive and of high quality. All KPIs have been reached and, on top of that, significantly exceeded in many cases. The sustainability of the results seems to be ensured and even the commercialization is looking promising.