The Digital Twin is the digital image of a physical object or system, which can be a product, a production plant, but also a company or a process. The Digital Twin connects virtual planning and development models with the real product or production world in order to give people a better insight into the system and its condition or behavior. A vision in the sense of Industrie4.0 is to enable technically complex systems to control themselves autonomously and behave more intelligently through digital algorithms, virtual models and status information.
The functional relationships of a product or a production plant are defined based on customer requirements and in consideration of a multitude of legal requirements in product planning and development. Without knowledge of these interrelationships, the operating data that the real asset captures and provides in its later product life cannot be interpreted correctly. If you do not know how a machine or system is actually supposed to function, it is not possible to identify the causes of deviations from this target state or behavior beyond doubt and take appropriate countermeasures. At the same time, knowledge of the history of origins is also important in order to be able to assess for what reason, for example, a bearing has failed and which other machines could also be affected by the problem.
This connection between the real asset and the development and planning models describing its history is called a digital thread. It is the digital "red thread" that links the information of a real product instance across processes and IT systems. On the one hand, this makes it possible to bring together all the information from the life cycle of the product instance or the real asset and thus forms the basis for the creation of a digital thread. Without a digital thread, the digital twin can be reproduced manually, but it is difficult or impossible to keep it up to date. On the other hand, traceability along the Digital Thread allows decisions in development and production to be questioned and optimization potential to be identified with the help of the operating data.