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Intelligent Motion Control under Industry4.E (IMOCO4.E)

The mission of the IMOCO4.E project is to provide distributed edge-to-cloud motion control intelligence for a wide range of Human-in-the-Loop CPS involving actively controlled moving elements

IMOCO4.E targets 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 the project are​ digital twins and AI principles (machine/deep learning). The subsequent mission 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 simulated or 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 semicon, packaging, industrial robotics and healthcare. Additionally, the project demonstrates the results in other generic “motion-control-centred” domains. The project outputs will affect the entire value chain of the production automation and application markets.

Sponsor
BMBF
Promoter
European Comission
Duration
01.09.2021 to 31.08.2024
Cooperation Partner
SIOUX CCM SIOUX (LE) NL, University of West Bohemia UWB (RTD) CZ, Brno University of Technology BUT (RTD) CZ, Fundacion Tekniker TEK (RTD) ES, FAGOR Aotek S. Coop. FAG (RTD) ES, ITML G.P. ITML (SME) GR, Tyndall, Uni. College Cork (UCC) TNI (RTD) IR, Gefran SpA GEF (LE) IT, Seven Solutions 7SOLS (SME) ES, Universidad de Granada UGR (UNI) ES, Intrasoft INTRA (LE) BE, REX Controls s.r.o. REX (SME) CZ, Emdalo EMD (SME) IR, Analog Devices ADI (LE) IR, Universita degli Studi di Brescia UNIBS (UNI) IT, University of Modena UNIMORE (UNI) IT, Evidence EVI (LE) IT, Elektronikas un datorzinātņu institūts EDI (RTD) LV, Universita degli Studi di Sassari UNISS (UNI) IT, Reden B.V. RED (SME) NL, Eindhoven University of Technology TUE (UNI) NL, Electromagnetic Compatibility MCC BV EMC (SME) NL, TNO TNO (RTD) NL, Philips Medical Systems PMS (LE) NL, International Iberian Nanotechnology Laboratory INL (RTD) PT, Edilasio Carreira da Silva ECS (LE) PT, Hahn-Schickard HS (RTD) DE, igitalTwin Technology DTT (SME) DE, uromedia Nur (SME) DE, IMST (SME) DE, STILL (LE) DE, Nexperia Nexperia (LE) NL, SOC-e SOC (LE) ES, PHILIPS CONSUMER LIFESTYLE BV PCL (LE) NL, VTT VTT (RTD) FI, CRIT CRIT (SME) IT,G.N.T. SYSTIMATA PLIROFORIKIS AE GNT (SME) GR, Siemens SIEMENS (LE) RO, Reexen REEX (SME) SUI, Fraunhofer IML IML (RTD) DE, MADARA Cosmetics AS Madara (SME) LV, Normet NOR (LE) FI, EXERTUS OY EXE (SME) FI, SEMI EUROPE GMBH SEMI EU (SME) DE, Philips Electronics NL BV PEN (LE) NL, Datalogic SRL DTL IT
Maturity Level
Research
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Competences

  • Software development
  • Sensor technology
  • Sensor fusion
  • State estimation
  • Signal processing