Harmonising and integrating the Digital Twins multiverse: A paradigm and a toolset proposal

Digital Twins are of paramount relevance in the Industry 4.0 framework. However, the idea of Digital Twin has many different interpretations. These are tied to the intended use of a Digital Twin, thus to the viewpoint of the involved professionals (process designers, control specialists, managers, and so on). The said interpretations are often highly incompatible with one another, since they can involve as heterogeneous entities as a CAD drawing and a neural network. A convergence of Digital Twin interpretations is desirable, to take full profit of the contained knowledge. In this research we argue that this desired convergence cannot be found at the same abstraction level of the available Digital Twin interpretations, and calls for a higher one. We consequently propose a paradigm – that we name Digital Multiverse – to comprehend the major Digital Twin interpretations not only in the sense of data integration, which is the goal of promising complementary ideas like that of Asset Administration Shell, but also by establishing and enforcing consistency rules that involve both data and models. We also show some examples to support the usefulness and viability of our proposal