Changing a factory is slow and risky. Re-planning a layout, replacing equipment, adapting to a disruption or ramping up a new product all take more effort and carry more uncertainty than is competitive today. Digital twins and digital threads are used to analyse, plan and monitor industrial systems, but rarely to operate and control them, which would mean moving large amounts of data in real time.
This impact area works on factories that use both measured and synthetic data to analyse increasingly complex systems with lower risk and in shorter time, and that treat repair and remanufacturing as first-class production. Understanding the validity of the models and AI processes that act on the data is part of the work, so that upscaling is robust.