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On December 3, 2002, Professor Michael Grieves of the University of Michigan clearly put forward the concept of digital twins at the kick-off meeting of the PLM Center for the first time. He called it “an idealized concept of PLM”. He believed that through the data of the physical device, a virtual entity and subsystem representing the physical device can be constructed in the virtual (information) space, and this connection is not one-way and static, It is connected throughout the life cycle of the product.
Digital twins, also known as “digital twins”, map the structure, state, behavior, function and performance of complex physical systems such as industrial products, manufacturing systems and cities to the digital virtual world, and carve, predict and control the physical system through real-time sensing, connection mapping, accurate analysis and immersive interaction, so as to realize the virtual and real integration of complex systems, so as to make the whole elements and process of the system The whole value chain reaches the maximum closed-loop optimization.

Digital twinning technology helps enterprises optimize, simulate and test in the virtual environment before they actually put into production, and also optimize the entire enterprise process synchronously during the production process, finally realizing efficient flexible production, rapid innovation and listing, and forging lasting competitiveness of enterprises.

Digital twinning technology is the key technology for manufacturing enterprises to move towards the strategic goal of Industry 4.0. It connects all stages (product creativity, design, manufacturing planning, production and use) by grasping the digital thinking of product information and its life cycle process, and connects to production intelligent equipment that can understand and respond to these information. Based on the basic state of physical entities, Digital Twin makes a highly realistic analysis of the established models and collected data in a dynamic and real-time manner for the monitoring, prediction and optimization of physical entities. In addition, digital twins, as edge side technology, can effectively connect the device layer and the network layer, become the knowledge extraction tool of the industrial Internet platform, and constantly transfer the fragmented knowledge in the industrial system to the industrial Internet platform. Digital twins with different maturity reassemble the industrial knowledge with different granularity, and call it through the industrial APP. Therefore, the industrial Internet platform is the incubator of digital twins, which is an important scenario of the industrial Internet platform.