AI REGIO project is part of the European Commission’s I4MS initiative (ICT Innovation for Manufacturing SMEs), which fosters the integration of digital innovations by manufacturing SMEs in Europe in order to boost their competitiveness. I4MS is currently operating in its fourth phase. Since October 2020, AI REGIO is funded by the European Union Framework Programme for Research and Innovation Horizon 2020 under Grant Agreement n° 952003 for a duration of 36 months.
The AI Regio consortium
The AI Regio consortium has 36 full beneficiaries from 11 countries. This includes a strong collaborative network of 13 regions and their corresponding DIHs and Competence Centers, which actively involves regional authorities and agencies, a portfolio of several thousand SMEs and representing 15% of EU GDP. These 13 Regions consists of 4 Motor Regions (Auvergne Rhône Alpes, Catalonia, Baden Wurttemberg and Lombardia) and 9 Vanguard Regions (East NL, South NL, Navarra, Basque Country, Norte, Tampere, Slovenia, Friuli-Venezia-Giulia, Emiglia Romagna) and 19 DIHs. AI Regio conducts 17 large and 16 small application experiments in collaboration with regional SMEs under a common unified framework for ethical-social-business impact measurement, assessment, and benchmarking. These experiments are classified in 4 thematic clusters and have led to 64 AI-enabled technological assets.
Region East Netherlands in AI Regio
From the Region of East-Netherlands, OostNL and Radboud University (SKU) are part of the AI Regio consortium. Together, we developed the supportive framework of BOOST, the DIH for East-Netherlands and a Didactic Factory “Industrial sustainability”. From Radboud University, the department of Analytical Chemistry & Chemometrics (AC&C) successfully completed two large experiments in the clusters, a) Factory Efficient and Sustainable Manufacturing with Armac B.V. and b) Quality Control and Predictive Maintenance with Royal Eijkelkamp B.V..
For the case of Armac B.V., the team at SKU demonstrated the implementation of AI in optimizing heat demand in district heating system by integrating historical data, physics, and process expert information. The AI model developed by SKU led to an interactive dashboard showing several KPIs, including real-time status and predictions of energy demand and the associated costs and savings. This model was implemented in a pilot and will lead to further digitalization in the organization.
With Royal Eijkelkamp B.V., an AI-driven predictive maintenance system was developed for monitoring maintenance need for soil and water sensors in remotely located wells. This improved as-in scheduled periodic maintenance and strongly reduced operating costs of the sensor network. In addition, this collaboration allowed the organization to further develop more data-driven services.
“Thanks to this project and the achieved results, we can offer our customers an even more reliable sensor network (increased uptime). In our case, this can literally save lives (flood monitoring). Expand our sensor network further and only send a service technician when necessary.” Royal Eijkelkamp BV
Radboud University in AI Regio
The AC&C department at Radboud University has a long-standing history of collaborations with SMEs in the region, promoting data-driven innovations in industry to match cost reductions with increased sustainability. The department is active in several public-private partnerships, bilateral partnerships, and national and European projects. Their expertise lies in integrating process knowledge with data-driven models to provide transparent dynamic models that enable optimizing the partner’s processes. Such models are customized and adaptable to process specific environments in manufacturing-, chemical-, and food industry. The AI Regio collaboration with Armac BV and Royal Eijkelkamp BV allowed RU to demonstrate how fundamental academic solutions may create practical industrial value, and further build their repertoire of software assets. The two projects provided data-driven quantitative insights for decision making and process optimization supporting automation and digitalization.
SKU hosts a didactic factory Industrial Sustainability for teaching and development of AI for Industry 4.0 and beyond. The didactic factory offers a summer course as well as more tailored specialized teaching of data science for process and manufacturing industry, to create sustainability and economic benefits. This didactic factory is linked to the DIH East-Netherlands and is an important platform for collaborations with manufacturing, chemical and process industry in the region.
Interested in knowing more about new digital solutions or developing partnerships to enable data-driven services? contact Chris Willamsen (Oost NL) or Jeroen Jansen/Neha Awasthi (Radboud University)
