From Digital Twins to Digital Twin Prototypes: Concepts, Formalization, and Applications

TL;DR

This paper formalizes the digital twin concept using Object-Z, introduces a digital twin prototype approach for embedded software testing, and demonstrates its application through real-world case studies in ocean observation and smart farming.

Contribution

It provides a formal definition of digital twins and prototypes, along with a practical approach for testing embedded systems in virtual environments.

Findings

Digital twin prototypes enable virtual testing of embedded systems.

The approach supports agile verification in CI/CD pipelines.

Real-world case studies validate the effectiveness of the method.

Abstract

The transformation to Industry 4.0 also transforms the processes of how we develop intelligent manufacturing production systems. To advance the software development of these new (embedded) software systems, digital twins may be employed. However, there is no consensual definition of what a digital twin is. In this paper, we give an overview of the current state of the digital twin concept and formalize the digital twin concept using the Object-Z notation. This formalization includes the concepts of physical twins, digital models, digital templates, digital threads, digital shadows, digital twins, and digital twin prototypes. The relationships between all these concepts are visualized as UML class diagrams. Our digital twin prototype (DTP) approach supports engineers during the development and automated testing of complex embedded software systems. This approach enable engineers to test embedded software systems in a virtual context, without the need of a connection to a physical object. In continuous integration / continuous deployment pipelines such digital twin prototypes can be used for automated integration testing and, thus, allow for an agile verification and validation process. In this paper, we demonstrate and report on how to apply and implement a digital twin by the example of two real-world field studies (ocean observation systems and smart farming). For independent replication and extension of our approach by other researchers, we provide a lab study published open source on GitHub.