Smarter systems due to DIGITAL TWIN
The development of reliable and agile digital twins of physical high-tech systems and materials is key to enabling shorter time-to-market, zero-defect & flexible manufacturing systems with accurate predictive maintenance. This crucial development is currently hampered by the lack of synergy between model-based engineering and data-driven/artificial intelligence approaches. Currently, data analytics approaches are lacking a link to the underlying physics of the high-tech systems and materials, which disqualifies them for real-time decision making.
DIGITAL TWIN will develop a smart and flexible value chain of high-tech systems and materials by the integration of data-driven learning approaches and model-based engineering methods.
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