A Pattern Catalog for Augmenting Digital Twin Models with Behavior
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Digital Twins are emerging as a solution to build and extend existing software systems to make better use of data produced by physical systems. For supporting the development of Digital Twins, several software vendors are
offering dedicated tool support, often referred to as Digital Twin platforms. The modeling capabilities of these platforms are mostly concerned with structural viewpoints, i.e., providing an overview of available components including their current and historical sensor values.
However, behavioral viewpoints did not yet receive much attention on these platforms. As behavioral models are often used during the design processes, e.g., for simulation and synthesis, it would be beneficial for having them included in Digital Twin platforms, e.g., for
reasoning on the set of possible next actions or for checking the execution history to perform runtime validation. In this paper, we present a catalog of modeling patterns for augmenting Digital Twin models with behavioral models and their corresponding runtime information
without requiring any extension of the code bases of Digital Twin platforms. We demonstrate the presented modeling patterns by applying them to the Digital Twin platform offered by Microsoft, in an additive manufacturing use case of a 3D printer in a production line.