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Two complementary methods to support the comparison and application-oriented assessment of AAS are presented, whereby set-theoretic operations are employed to compare AAS models, enabling the identification of common, missing, and differing submodels and parameters.
Unlock the full potential of digital twins by understanding the best software architectures for integrating AI-powered services directly into Asset Administration Shells.