Intelligent Motion Control under Industry 4.E
IMOCO4.E provides vertically distributed, edge-to-cloud intelligence for machines, robots and other human-in-the-loop automation 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.
The project develops a way to understand complex machines and robots through two main pillars: digital twins and AI principles (machine learning/deep learning). These pillars build on a completed ECSEL JU project, I-MECH, and uses its reference framework and methodology by adding new tools to layer 3 that deliver an intelligible view on the system, from the initial design throughout its entire life cycle. For effective employment, completely new demands are created on the Edge layers (Layer 1) of the motion control systems (including variable speed drives and smart sensors) which cannot be routinely handled via available commercial products.
This project brings adequate edge intelligence into the Instrumentation and Control Layers, to analyse and process machine data at the appropriate levels and to synchronise the digital twins with either the simulated or the real-time physical world. At all levels, AI techniques are employable.
IMOCO4.E will deliver a reference platform consisting of AI and digital twin toolchains, and a set of mating building blocks for resilient manufacturing applications. 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, and additionally in other generic motion-control-centred domains. The project outputs will affect the entire value chain of the production automation and application markets. By further evolving the I-MECH methodology, it creates new, sustainable propositions such as “digital twins as a service” or “(generative) machine design as a service”, for the ongoing smartification of industries.