Open-Source Frameworks for Hierarchical Digital Twins in Edge-Cloud Environments

In recent years, digital twin technologies have become a game-changing technology to create universally interoperable systems that digitally represent physical entities. These new approaches prove to be especially valuable in the world of Industry 4.0, where they enable companies to simulate, optimize, and manage manufacturing processes in a completely isolated virtual environment. By providing these digital representations of physical assets, digital twins provide real-time forecasting, monitoring, control, and advanced decision-making. However, despite their immense potential, the implementation and utilization of digital twins in industrial environment come with challenges. In particular, the problems come in scaling and managing heterogeneous environments. To address these challenges, in this thesis, we propose a middleware platform named OmniTwins designed to facilitate data integration and scalability in industrial environments. Concerning focus on providing accurate digital representation of physical assets, offering a flexible and structured approach to handling the virtual counterparts of real-world entities. The main features of OmniTwins include support for heterogeneous IoT communication protocols, uniform data representation management interfaces to improve interoperability, and a focus on scalability and flexibility. The ultimate goal of the platform is to link the gap between the physical and digital worlds. The aim is to develop more intelligent, efficient, and resilient industrial systems. The platform is still in need of implementation and validation in a real production environment. By persisting with innovation and validation of these technologies, OmniTwins sets the stage for more intelligent and efficient industrial ecosystems in the Industry 4.0 era.