Intelligent Motion Control under Industry 4.E

Project: EU project

Project Details


The IMOCO4.E target is to provide vertically distributed edge-to-cloud intelligence for machines, robots and other human-in-the-loop cyber-physical systems having actively controlled moving elements. They face ever-growing requirements on long-term energy efficiency, size motion speed, precision, adaptability, self-diagnostic, secure connectivity or new human-cognitive features. IMOCO4.E strives to perceive and understand complex machines and robots. The two main pillars of this project are digital twins and AI principles (machine learnging/deep learning).

These pillars build on the IMECH reference framework and methodology, by adding new tools layers that delivers an intelligible view on the system, from the initial design throughout its entire life cycle. For effective employment, completely new demans are created on the Edge layers of the motion control systems (including variable speed drives and smart sensors) which cannot be routinely handled via available commercial products.

On the ground of this, the subsequent mission of this project is to bring adequate edge intelligence into the Instrumentation and Control Layers, to analyse and process machine data at the appropriate levels of the feedback control loops and to synchronise the digital twins with either the simulated or the real-time physical world. At all levels, AI techniques are employable.

Summing up, IMOCO4.E strives to deliver a reference platform consisting of AI and digital twin toolchains and a set of mating building blocks for resilient manufacturing applications. The optimal energy efficient performance and easy (re)configurability, traceability and cyber-security are crucial. The IMOCO4.E reference platform benefits will be directly verified in applications for semiconductor, packaging, industrial robotics and healthcare. The project outputs will affect the entire value chain of the production automation and application markets.
Effective start/end date1/09/2131/08/24

Collaborative partners

  • VTT Technical Research Centre of Finland
  • Evidence Srl (Project partner)
  • Still GmbH (Project partner)
  • Sioux Technologies B.V. (Project partner) (lead)
  • Siemens Industry Software Srl România (Project partner)
  • Gefran Drives and Motion Srl (Project partner)
  • Edilásio Carreira Da Silva Lda (Project partner)
  • AS MÁDARA Cosmetic (Project partner)
  • DigitalTwin Technology GmbH (Project partner)
  • Fundación Tekniker (Project partner)
  • Netherlands Organisation for Applied Scientific Research (TNO) (Project partner)
  • Information Technology for Market Leadership Pc (ITML) (Project partner)
  • Cybertron Tech Gmbh (Project partner)
  • Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e. V. (Project partner)
  • REX Controls s.r.o. (Project partner)
  • System-on-Chip engineering S.L. (Project partner)
  • University of Granada (Project partner)
  • Reden B.V. (Project partner)
  • INTRASOFT International N.V. (Project partner)
  • Philips Consumer Lifestyle B.V. (Project partner)
  • Brno University of Technology (Project partner)
  • Seven Solutions S.L. (Project partner)
  • FAGOR Automation S. Coop. (Project partner)
  • G.N.T. Information Systems S.A. (Project partner)
  • Nuromedia GmbH (Project partner)
  • IMST GmbH (Project partner)
  • University of Sassari (Project partner)
  • Philips Electronics Nederland B.V. (Project partner)
  • Hahn-Schickard-Gesellschaft für angewandte Forschung e.V. (Project partner)
  • SEMI Europe GmbH (Project partner)
  • Normet Oy (Project partner)
  • Nexperia BV (Project partner)
  • Institute of Electronics and Computer Science (EDI) (Project partner)
  • Emdalo Technologies Ltd (Project partner)
  • University of West Bohemia (Project partner)
  • Exertus Oy (Project partner)
  • Philips Medical Systems Nederland B.V. (Project partner)
  • Eindhoven University of Technology (TU/e) (Project partner)
  • Datalogic S.r.l. (Project partner)
  • International Iberian Nanotechnology Laboratory (INL) (Project partner)
  • University of Modena and Reggio Emilia (Project partner)
  • Centro di Ricerca e Innovazione Tecnologica s.r.l. (Project partner)
  • University College Cork (Project partner)
  • University of Brescia (Project partner)
  • Electromagnetic Compatibility MCC B.V. (Project partner)
  • Analog Devices International Unlimited Company (Project partner)

Funding category

  • EU-H2020


  • H2020-ECSEL-2020-2-RIA-two-stage
  • Artificial intelligence
  • intelligent systems
  • multi agent systems