Digital twinning and meta universe duality are the mapping of meta universe in the field of production and manufacturing.
Digital twin can be regarded as industrial meta universe: promote the closed-loop optimization of the whole industrial business process in the digital twin model through real-time IOT data, and continue to modify and improve the physical model through data. With the maturity improvement of industrial Internet, edge computing, 5g, cloud computing and other technologies, digital twins are expected to gradually move from concept to reality. The essence of digital twin is the closed-loop transmission of equipment recognizable identification, engineering personnel knowledge and experience and management key decisions in the system process, and finally realize the high-level intelligent transformation.
Digital twin includes connection layer, mapping layer and decision-making layer: the connection layer has the functions of acquisition, perception and feedback control, which is the key link of digital twin enabling manufacturing industry; The mapping layer has the functions of information exchange, model exchange and data mart. Based on the construction and integration of information model, it realizes the optimization of industrial communication and opens up the data island; The decision-making layer feeds back the instructions to the physical entity in a low-cost way to realize closed-loop control.
The application of digital twin is mainly based on discrete single scene and refinement: in the three directions of increasing the depth of digital twin, expanding the dimension of digital twin and refining the particle size of digital twin, the cumulative proportion of refined digital twin particle size is as high as 87%, far exceeding the other two directions. Through comprehensive analysis of the proportion of all directions, the digital twin landing applications in 2021 are mainly discrete single scene applications and refinement, while the full life cycle optimization and complex scene empowerment are insufficient, and the development level and maturity are at a relatively early stage.
Considering the application dimension, development maturity and enabling level of the digital twin, the application scenarios with the most investment value are material demand forecasting and yield improvement. On the other hand, digital twin has the highest practical score and the highest investment value in the production and safety links. The reason is that the production link involves a large number of equipment and has a high degree of automation, which requires high real-time performance. Digital twin can realize the real-time system at low cost, while the safety link is highly dependent on people, so digital twin simulation is urgently needed to reduce the cost.
