On Sept. 25, Nature published a comment of the Digital Twins Research Group from the School of Automation Science and Electrical Engineering online, entitled “Make More Digital Twins” (Nature 2019, 573: 490-491). The team leader, Prof. Tao Fei is the first and corresponding author, and his doctoral student Qi Qinglin is the second author.
The first and corresponding author: Tao Fei, a professor and tutor for PhD students in the School of Automation Science and Electrical Engineering, Beihang University
The second author: Qi Qinglin, a PhD candidate in the School of Automation Science and Electrical Engineering, Beihang University
The first institute: School of Automation Science and Electrical Engineering, Beihang University
With the proposal of manufacturing development strategy at the national level, such as “Industrial Internet” in US, “Industry 4.0” in German, “Manufacturer of quality” in China, smart manufacturing has become the common development trend and target in global manufacturing industry. As a main technology to solve the problem of combining cyber-physical system with smart manufacturing and to implement the idea as well as the goal of smart manufacturing, digital twins has been highly concerned and studied by academia, and has been widely introduced into more fields for applications by industry.
As one of the earliest digital twins teams, the Digital Twins Research Group led by Prof. Tao Fei, first put forward the concept of digital twinshop-floor (DTS) and published the first article about it (CIMS 2017, 23(1): 1-9). Meanwhile, the application of digital twins in manufacturing was jointly carried out by more than 20 universities and research institutes in China (CIMS 2018, 24 (1): 1-18). In addition, in order to realize the application of digital twins in industry, the research group of Beihang University has proposed the Digital Twins Five-dimension Model and explored its application, together with cooperative enterprises, in more than 10 aspects covering the satellite / space communication network, ships, vehicles, aircraft, power plants, manufacturing workshops, complex equipment, medical treatment, smart city and so on to meet the practical needs of enterprises (CIMS 2019, 25 (1): 1-18).
However, in the practical application of digital twins in manufacturing and other related fields, there are still a series of scientific problems and difficulties. For instance, some problems about the Digital Twins Five-dimension Model still exist (1) in the physical entity (PE) — how to realize smart perception and interconnection among multi-source heterogeneous physical entities, acquire real-time multi-dimension data of physical entity objects so as to deeply understand and discover relevant laws and phenomena, and then achieve reliable control and precise execution of physical entity; (2) in the virtual equipment model (VE) — how to construct dynamic multiple dimension, space and time high-fidelity model, how to ensure and verify the consistency / authenticity / validity / reliability between the model and the physical entity, and how to realize the assembly and integration of multi-source, multi-disciplinary and multi-dimension models; (3) in the DT data model (DD) — how to realize the real-time acquisition and efficient transmission of all-factor / all-business / all-process multi-source heterogeneous data, how to deeply integrate and comprehensively synthesize the cyber-physical data, and how to achieve precise mapping and real-time interaction between digital twins data and physical entity, virtual equipment and services; (4) in Connection model (CN) — how to achieve real-time interaction across protocols / interfaces / platforms, and how to realize iterative interaction and dynamic evolution among data, model, and application; (5) in Services model (Ss) — how to provide services based on multi-dimension model and twins data to meet the needs of different fields, different levels of users and different business applications, and to add value and efficiency in accordance with the service in need. Besides, there are other practical bottlenecks in how to achieve the collaboration of experts in different fields and disciplines, and how to realize the joint innovation of education, research, and industry. The comment studies and explains these related scientific problems and challenges.
In order to promote the development of digital twins technology and its application in manufacturing and other related fields, Beihang and 12 domestic universities jointly sponsored the First Academic Conference on Digital Twins and Smart Manufacturing Services in 2017, which has been successfully held for three consecutive sessions. Prof. Tao was invited to publish Digital Twin Driven Smart Manufacturing in Elsevier in 2018. In the past three years, he has been invited to make more than 30 reports on academic conferences related to digital twins held in countries such as the United States, Russia, Japan and the United Kingdom. His work, which has attracted wide attention from academia and industry at home and abroad, has been tracked and studied by over 100 universities and research institutes around the world, and has been applied by relevant enterprises.
The research of the Digital Twins Research Group from Beihang was supported by the National Natural Science Foundation of China (Nos. 51522501，51875030), Youth Talents Support Program of Beihang University, Beijing Municipal Science & Technology Commission (Z181100003118001), etc.
Reviewed by Tan Hualin
Edited by Jia Aiping
Translated by Zhao Yue
