This article introduces the market dynamics and trends of digital twin technology in China. Specifically, the article presents the market size, driving forces, applications and challenges in the competitive landscape. Also, it aims to bring you unique insights from industry experts.
Background
NASA first applied digital twin technology to simulate, emulate and predict aerospace metrics, which was extremely expensive at the time. After the technology became more mature and affordable, China became the biggest beneficiary of this technology. Under the continuous derivation of policy, the ecology of Chinese digital twin enterprises is blooming.
Additionally, with the rise of digital twin technology in manufacturing and the need to make sense of ever-growing data sets, digital twin technology is becoming the focus of national priority. However, with nebulous definitions, the term 'digital twin' is often seen as a buzzword that more frequently needs clarification.
This article sets out to analyze digital twin market dynamics with a detailed definition to alleviate confusion while demonstrating the value of digital twin technology to businesses.
What Is Digital Twin
The digital twin is a dynamic digital informational model that represents real-world objects. Digital twin uses real-time data, allowing stakeholders to monitor the performance and lifecycle of a project. Digital twin technology involves digital support, twin construction, and human-computer interaction. These technologies enhance real-time precision, flexibility and interactivity. The establishment of digital twins can be divided into four steps: data acquisition and processing, data modeling, simulation, and prediction analysis. In this process, digital twin solution providers mainly focus on integrating multi-source data, three-dimensional visualization rendering and simulation analysis scene construction. Digital twin technology could help engineers alter the prototype's design at any time during the design process more quickly and with fewer human resources. To be more specific, digital twin allows manufacturers to investigate performance problems throughout the delivery process and produce valuable insights.
Market Size and Driving Factors
In 2021, China's digital twins market scale reached CNY 2.73 billion, with a compound growth rate of up to 200% from 2019 to 2021. As data acquisition and iteration capabilities continue to improve, technologies such as CIM, geographic information, data modeling and simulation will become more mature and integrated with other applications. The digital twin market will grow faster. It is expected that China's digital twin market will exceed CNY 6 billion by 2023.
The growing use of digital twin technology in the manufacturing sector and technological advancement are two main driving factors of the digital twin market. The manufacturing industry predominantly adopts the 2D designing process. However, it is slowly taking steps toward using digital twin technology to cut costs and enhance on-site visualization. Unplanned downtime and production inefficacity are two significant problems impacting manufacturers, and digital twin technology is the ideal solution. It helps manufacturers search for a system that can predict potential flaws and malfunctions to prevent downtime and improve efficiency.
In 2021, the scale of China's core computing power industry reached CNY 1.5 trillion, and the growth of AI computing power ranked first in the world, providing a strong impetus for the digital twins.
Industry Chain and Applications
The upstream of the digital twin industry contains equipment, networks and computing power. The midstream mainly consists of a digital twin platform construction process, and the downstream primarily comprises different application scenarios, such as smart city, smart manufacturing, intelligent energy and smart healthcare. This article will discuss four major fields using digital twin technology, as they generate the biggest impacts on society.
In the Industrial field, predictive maintenance, quality testing, process optimization and shop scheduling can be carried out based on digital twin. These applications are considered critical in industrial Internet and intelligent manufacturing, covering research, design, production, operation, management and after-sales service.
In the Urban field, The exploration of digital twin cities has become a consensus of local governments, involving scenarios such as intelligent emergency response, smart construction sites and storm flood simulation. From the distribution of the application scenarios of digital twins in the construction of digital cities in the second quarter of 2022, water conservancy, energy and integrated urban management are the most widely used.
In the Medical field, the digital twin is showing promising applications in drug testing, compound discovery, outcome prediction and surgical collaboration. The exploration of digital twin hospitals and digital twin hearts has been actively carried out.
In the Transportation field, relying on digital twin technology can realize the maintenance of traffic infrastructure, traffic scheduling optimization, safe driving, etc. Digital twin applications such as bridge health maintenance and traffic scheduling optimization are being deepened.
Challenges
Some of the challenges within the field of digital twin technology are listed below:
(1). Security challenges. Digital twin brings together massive data sets and puts higher requirements for data security protection. For example, digital twin cities have a wide range of data sources and high data concentration. Urban infrastructure is highly dependent on the operation of data. Once invaded, the security of this place will be excellent, and the process of the whole city will be paralyzed instantly. In addition, the data in cities involve citizens' privacy, which needs to be effectively protected.
(2) Real-time challenge. In the case of high real-time demand, model simulation and verification will extend the system's running time on the digital twin network. Therefore, different processing mechanisms must be added in different network application scenarios to further improve hardware and software performance requirements.
(3) Coordination difficulties. It is difficult for multiple departments to coordinate, the threshold of data collection is high, the construction of information infrastructure needs to be balanced, and the application level and depth need to be more.
Enterprise Analysis & Insights
According to Asia Pacific Digital Twin Market Forecast 2026 published by Graphical Research, the Asia Pacific digital twin market size is slated to grow considerably and amass US$11 billion by 2026. There are now more than 700 enterprises related to digital twin technology in China, and one of them is DataMesh.
DataMesh is a leading company of metaverse platforms based on digital twin and XR technology. DataMesh, with an R&D center in Beijing, is one of the few companies in China with tool platforms designed for manufacturing enterprises, aiming to empower 400 million industrial workers in China and 2 billion worldwide. The company upgrades services such as industrial Internet and digital building transformation, breaking the barrier of spatial data processing and real-time 3D collaboration, enabling companies to benefit from modern workspace technology and increase productivity. Currently, the products of DataMesh are exported to Japan, Taiwan, Southeast Asia and other markets.
According to Li Jie, the CEO of DataMesh, digital twin technology has yet to be widely known by the general public, and the perception of customers largely determines the cost of data. In countries such as Japan, the United States, and Europe, corporate executives' strong awareness of the digital twin is a driving factor in developing this technology. Though the data cost has been dramatically reduced with the introduction of open design, the digital twin technology will be applied even more broadly with raised public and industry awareness in China, which is aligned with his belief that the digital twin technology is ultimately for the frontline workers and not just for leaders.
About the Interviewee:
Li Jie, founder & CEO of DataMesh, graduated from Nanjing University and received his master's degree from Tongji University. Before founding DataMesh, Li Jie worked for Microsoft China and Microsoft US headquarters for 8 years, focusing on enterprise services. He led the design and development of several core projects such as Office 365 SharePoint and Data-Driven Experience as the product manager.