1/09/21 – 30/08/24 (36 months)
9.072.996,63 €
H2020
ECSEL-2020-2-RIA
SIOUX TECHNOLOGIES BV
Machines, robots and other human-in-the-loop cyber-physical systems having actively controlled moving elements face ever-growing requirements on long-term energy efficiency, size, motion speed, precision, adaptability, self-diagnostic, secure connectivity or new human-cognitive features. The IMOCO4.E target is to provide vertically distributed edge-to-cloud intelligence for them.
Thanks to the collaboration with 50 academic and industrial partners at the European level, 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, modularity, traceability and cyber-security are crucial.
The IMOCO4.E reference of the platform benefits will be directly verified in applications for semiconductor, packaging, industrial robotics and healthcare. Additionally, the project demonstrates the results in other generic “motion-control-centred” domains. Project outputs will affect the entire value chain of the production automation and application markets. Through the further evolved I-MECH methodology, it creates a sustainable proposition, such as “digital twins as a service” or “(generative) machine design as a service”, for the ongoing smartification of industries and shortening of innovation cycles. The motion control parts to be developed, modelled and used shall become (more) uniform in their description to allow faster integration in the design flow and as such more modular to serve exchangeability during the lifecycle of the systems created.
CRIT leads Pilot 3, which focuses on the improvement of state-of-the-art packaging machines leveraging on the technologies to be developed in IMOCO4.E.
The main objective of this pilot is to assess the feasibility of improving automatization for quality checks and alarm detection throughout a whole high-speed packaging process. In this perspective, the AI based machine vision technology in combination with the Smart control platform will help to ensure good quality output. Real-time condition monitoring, to enable prompt reaction to possible alarms, and secure communication will be also ensured.