DIGIT BRAIN

Experiments conducted using DIGITbrain should use modeling, simulation and/or machine learning technology to create a digital twin.
Building on the Digital Twin concept, the experiments will focus on enabling the customization of industrial products (intended as systems operated by manufacturing companies to support the production of final consumer products) and facilitating cost-effective distributed and localized manufacturing for manufacturing or medium-sized SMEs, using edge, cloud-based modeling and HPC, simulation, optimization, analysis and machine learning tools. Experiments can cover any segments across the entire manufacturing sector, including (but not limited to) discrete manufacturing, continuous manufacturing, or construction. Experiments should aim to take into account the development and uptake of digital technologies, especially in segments where they are underused.
Experiments can be on different innovative use cases in different production segments. They should be aimed at improving operation, industrial product life cycle and/or environmental impact. Experiments are expected to take into account the environmental effects of their results from the outset.
Experiments are expected to apply to any segment of the manufacturing sector, including (but not limited to) discrete manufacturing, continuous manufacturing, or construction. Experimentation should aim to take into account the development and use of digital technologies, especially in segments where they are underused. According to the DIGITbrain solution, experiments should model the behavior of an industrial product (production machine, line or mechatronic system) using a digital twin. In addition, the experiments are to demonstrate benefits in different phases of the industrial product life cycle, its adaptation and/or evolution to new generations of the industrial product. Experiments should also take environmental impact into account. The software that will be used in the experiment is expected to already exist, either open source or proprietary. Experiment partners should have access to the source code or programming interface so that the needs of the experiments can be adapted to the DIGITbrain platform.
The third part of the experimentation, carried out under the 2nd call, is planned to attract new third parties (SMEs and mid-caps) and conduct experiments to extend and validate the DIGITbrain solution under development to increase the competitiveness of SMEs and mid-caps by transferring innovative solutions to the wider production community.
Third parties: Manufacturing End Users (will conduct experiments. Preferably SMEs but also mid-caps), Independent Software Vendors (ISVs), Engineering or Software Consultants, Research Organizations, High Performance Computing (HPC) providers, any organization , which will act as a Digital Innovation Hub (DIH).
Requirements for consortia: The minimum number of partners in an experimental consortium must include: one end-user (mainly SMEs); and one technical partner acting as an independent software vendor (ISV), software engineer or consultant.
Proposal language: the experiment proposal and all documentation must be in English.
Budget: Financial support to third parties: EUR 684,600. It is planned that financial support will be allocated to the implementation of a maximum of 7 experiments. Planned contribution per experiment EUR 97,800. The maximum amount of financial support awarded to one third party per experiment may not exceed EUR 60,000. According to EC rules, no third party may receive more than EUR 100,000 from I4MS and SAE open calls under the Horizon 2020 programme.
Time frame: applications can be sent back until May 31, 2022, at 17.00. The duration of participation in the experiment is 12 months from October 1, 2022 to September 31, 2023.