Digital twins have become a common requirement for digital construction in multiple industries.

Since the concept of digital twins has been generalized by everyone, various interpretations have appeared for a while. Some digital twin projects actually do 3D visualization, or collect sensor data into the information system for synchronous display, and some digital twin projects are actually algorithmic requirements. Everyone has their own understanding of this, which has caused confusion in the current digital twin construction.

In fact, as an enterprise or this industry, digital twins are the most effective way to enter the digital world. Instead of doing projects to make some effects and political achievements, it is better to build the ability of digital twins in a down-to-earth manner. It is to enable enterprises to have the dual capabilities of building and using digital twins.

So how do we evaluate the ability of an organization’s digital twin? This is what I will introduce to you today.

Digital Twin Capability Levels

The digital twin capability level is divided into 5 levels.

Level 1: Twin Body Construction

At this stage, the main construction goal should be to look like a model, which is to build a model consistent with the real space in the virtual space, which we call a twin. Twin body construction is not equivalent to 3D model construction, and its construction should be based on four dimensions. The four dimensions are geometric model, physical model, behavioral model, and rule model.

Geometric models: aim to look like. Dimensions, proportions, shapes, colors are the main content of its construction.

Physical model: mainly to solve the material problem, whether it is metal or plastic, whether it is elastic or not.

Behavior model: mainly for the basic setting of the operating mechanism, such as whether it can be rotated.

Rule model: Mainly make basic settings for simulation operation, such as: maximum speed, maximum opening and closing angle, etc.

The construction of a twin should start from basic twins such as parts, and through the modeling ability, the scattered twins of parts can be assembled into equipment or higher-level twins in virtual space. So this is the embodiment of twin body building ability. A single data source is anchored by the geometric model, and twin models are built at multiple levels such as components, subsystems, systems, and systems of systems to provide an objective reference standard for each participant.

In this ability level, the ability to build twins and manage twins is the main performance.

The second level: data simulation and digital-analog synchronization capacity building

The construction at this stage is one of the most challenging tasks in digital twin capacity building. A simple 3D visualization, in addition to providing managers with intuitive and visible data or scenes, cannot effectively support the operation of the virtual space. The data simulation and data synchronization link the data with the twin, use the data to describe the state of reality and superimpose it in the virtual space, which will give more value to the twin space.

This level of digital twinning may be the norm for high-end manufacturing, but for a large number of low-end industries or construction, urban, energy and other fields, the cost of using traditional simulation tools is often too high to have practical application value, which means , the application requirements of digital twins in multiple industries require the construction of low-cost data description tools.

The third level: twin body and twin scene fusion

At this stage, the fusion of twin scenes and twin bodies is realized to form a rich twin digital ecology, and equipment or products are integrated into virtual space scenes to realize the common digitalization and twinning of the two. And further establish the key interaction between the physical world and the digital world at this stage. This is the difficulty of advanced digital twin construction.

Level 4: Twin Capabilities of Dynamic Simulation and Running Simulation

The fourth level of digital twinning is to add process twinning capabilities on the basis of previous capabilities. That is, the product operation characteristics of the dynamic twin physical world is a dynamic virtual world. Under this capability, the process of construction and operation has also completed the twinning process. .

Digital twinning at this stage has greater challenges, not only including hardware twins, but also adding the concept of management twins and the concept of timeline. It is necessary to contribute management data, equipment operation data, product operation data, etc. and to twin and fuse the data. That is, in some scenarios, use data + algorithm + drive to realize twin management and reverse control, and reversely support the production and management activities in the real world from the twin world.

Level 5: Full-scenario autonomous twin

Full-scenario autonomous digital twinning can be understood as realizing the first-level to fourth-level digital twinning work by itself according to various environmental changes. At present, there are no specific cases that have been realized. Its development will take a long time, and it needs to rely on the development of other technologies, such as: cloud computing, big data, algorithms, etc.

To quote a passage:

If digital twinning develops to be able to realize the first-level to fourth-level digital twinning work by itself according to various environmental changes, then it has reached the highest level of autonomous twinning. Such a goal requires the realization of data automation and needs to be established on the basis of digitization, networking and intelligence.

Undoubtedly, artificial intelligence, Internet of Things, and data science will play a crucial role in this level. So far, the relevant theories and technologies have not yet matured, and only some relatively simple applications have appeared. For example, NASA has produced some concepts in the space manufacturing system, and currently only has some breakthroughs in the additive manufacturing model, but it will take decades of hard work to really reach that level.

Digital twin technology is the basic part of digital twin. Its implementation degree determines the application effect of digital twin. In different industries, the level of digital twin has different judgment standards. The above is just a summary of the basic concepts and characteristics. Description, follow-up need to make corresponding adjustments according to specific application scenarios.

From the perspective of traditional disciplines or research fields, the first three levels of digital twinning are currently mature and are actively being implemented. The fourth and fifth levels corresponding to dynamic twins and autonomous twins require the participation of new-generation technologies such as dynamic data-driven and artificial intelligence, especially dynamic data-driven simulation, which has become the place where experts and scholars strive for breakthroughs in the past ten years. This is also one of the main research areas of digital twins.