The digital twin as a common knowledge base in DevOps to support continuous system Evolution

There is an industry wide push for faster and more feature rich systems, also in the development of Cyber-Physical Systems (CPS). Therefore, the need for applying agile development practices in the model-based design of CPS is becoming more widespread. This is no easy feat, as CPS are inherently complex, and their model-based development is less suited for agile development. Model-based development does suit the concept of digital twin, that is, design models representing a system instance in operation. In this paper we present an approach where the digital twins of system instances serve as a common-knowledge base for the entire agile development cycle of the system when performing system updates. Doing so enables interesting possibilities, such as the identification and detection of system variants, which is beneficial for the verification and validation of the system update. It also brings along challenges, as the executable physics based digital twin is generally computationally expensive. In this paper we introduce this approach by means of a small example of a swiveling pick and place robotic arm. We also elaborate on related work, and open future challenges.