Cloudification of Production Engineering for Predictive Digital Manufacturing


Information and Communication Technology (ICT) is essential for the digitalization of the manufacturing sector; notwithstanding, less than 25% of the manufacturing companies in Europe profit from ICT-enabled solutions. In order to democratically boost the competitiveness of the European manufacturers (especially Small and Medium-sized Enterprises - SMEs), innovative solutions need to consider technological and commercial scalability from the beginning. From this perspective, the cloudification of services has become the ideal enabler in the manufacturing digitalization. Successful European initiatives such us CloudFlow, cloudSME or Fortissimo have demonstrated the benefits of cloudification for engineering services, by means of combining HPC resources, computational tools, and cloud computing platforms. Manufacturing SMEs are empowered to compute and solve problems that cannot be tackled without cloud and HPC technology, making them more competitive by reducing development times for innovative product with better performance. The results of these initiatives are fostering the engineering and to some extend the prototyping processes within the manufacturing workflow; however, monitoring and optimizing production processes have not yet greatly benefited from an integrated information workflow and simulation loop based on on-line factory data. The core partners of CloudFlow ( and cloudSME ( are joining forces to leverage factory data with cloud-based engineering tools: a) paving the way toward manufacturing analytics, b) enriching the manufacturing engineering process with on-line data, and c) simulating and optimizing the production process with the vision to support it in real-time. The consolidated platform between CloudFlow and cloudSME with extended capabilities to process factory data is going to be accessed through a central interface, enabling the stakeholders to interact, and collaborate.

Project details

Unibo Team Leader: Flaviano Celaschi

Unibo involved Department/s:
Dipartimento di Architettura
Centro Interdipartimentale di Ricerca Industriale su Meccanica Avanzata e Materiali

Fraunhofer Ipa(Germany)

Other Participants:
Privredno Drustvo Za Pruzanje Usluga Istrazivanje I Razvoj Nissatech Innovation Centre Doo (Serbia)
Insomnia Consulting (Spain)
Lunds Universitet (Ulund) (Sweden)
Linz Center Of Mechatronics Gmbh (Austria)
ALMA MATER STUDIORUM - Università di Bologna (Italy)
Consorzio CETMA - Centro di Progettazione, Design & Tecnologie dei Materiali (Italy)
Catmarine Srl (Italy)
Stam Srl (Italy)
Cloudsigma Ag (Switzerland)
FERRAM STROJIRNA, s.r.o. (Czech Republic)
MAGYAR TUDOMANYOS AKADEMIA SZAMITASTECHNIKAI ES AUTOMATIZALASI KUTATOINTEZET-Institute for Computer Science and Control of the Hungarian Academy of Sciences (Hungary)
Deutsches Forschungszentrum Fur Kunstliche Intelligenz Gmbh (Dfki) (Germany)
machineering GmbH & Co. KG (Germany)
Stiftelsen Sintef (Norway)
Hydal Aluminium Profiler as (Norway)
Nabladot Sl (Spain)
Supsi Scuola Universitaria Professionale Della Svizzera Italiana (Switzerland)
University of Westminster (United Kingdom)
CLESGO UG (haftungsbeschränkt) (Germany)
Innomine Group Kft (Hungary)
Cooperlat Soc.Coop.Agr. (Italy)
Ska Polska Sp Z O. O. (Poland)
Endef Engineering Sl (Spain)
Cloudbroker Gmbh (Switzerland)
The University Of Nottingham (United Kingdom)
Vsb Technical University Of Ostrava (Czech Republic)
Cloudsme Ug (Germany)
DSS Consulting Informatikai és Tanácsadó Kft. (Hungary)
Zannini-Spa (Italy)
Scaletools Ag (Switzerland)
Bakony Elektronika Kft. (Hungary)

Total Eu Contribution: Euro (EUR) 8.712.521,27
Project Duration in months: 42
Start Date: 01/10/2017
End Date: 31/03/2021

Cordis webpage
Project website

Industry, innovation and infrastructure This project contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 768892 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 768892