Since 2019, two concepts have been hotly debated in the A-share market: edge computing and digital twins. Discussions surrounding digital twin technology reached a fever pitch, especially after the fatal crash of the Boeing 737 MAX 8 and the burning of Notre Dame Cathedral in Paris. Digital twins were also included in Gartner's 2019 list of top ten strategic technology trends. IDC predicts that by 2020, the world's top 600 companies will be using digital twins to drive product innovation. MarketsandMarkets predicts that the digital twin market will reach $15.7 billion by 2023, growing at a CAGR of 38%. The future prospects for digital twins are vast.
Digital twins drive intelligent manufacturing
The advantages of digital twins in manufacturing are significant. There's a saying in industry that digital twins represent a "1% revolution in the industrial sector," meaning that a 1% increase in global industrial productivity can reduce costs by $30 billion. According to Gartner, "By 2021, half of the large industrial companies will be using digital twins, thereby increasing the effectiveness of these organizations by 10%."
Digital twins, through design tools, simulation tools, and the Internet of Things (IoT), map various attributes of physical equipment into a virtual space, forming a detachable, replicable, modifiable, and deletable digital image, thus improving operators' understanding of the physical entity. This will facilitate production and shorten production cycles. Furthermore, by gaining real-time access to target perception data and leveraging predictions and analyses of empirical models, digital twins can calculate and summarize some immeasurable indicators through machine learning, significantly enhancing the understanding, control, and prediction of machinery and processes.
Therefore, by gaining a deep understanding, making correct inferences, and operating precisely on objects in both physical and logical spaces, digital twins can improve the efficiency of design, operation, control, and management.
Product-oriented digital twin applications focus on optimizing the entire product lifecycle. For example, AFRL collaborated with NASA to build a digital twin of the F-15, using data from the entire lifecycle of the fighter jet—flight testing, production, and maintenance—to correct simulation process mechanisms and improve the accuracy of airframe maintenance early warnings.
Digital twin applications for the workshop focus on the control of the entire production process. For example, Airbus created a digital twin of the A350XWB final assembly line by installing RFID on key tooling, materials and components, making the industrial process more transparent and enabling the prediction of workshop bottlenecks and optimization of operational performance.
Virtual verification enables the simulation of products, production lines, and logistics in a virtual space to improve operational efficiency in real-world scenarios. For example, ABB's PickMaster Twin allows customers to test robot configurations on a virtual production line, enabling the verification and optimization of picking operations in a virtual space.
Opportunities and Challenges
Digital twins enable us to re-examine the potential flaws and innovation opportunities in traditional business models from a completely new, data-driven perspective. Especially with the further integration of traditional modeling and simulation technologies with IoT, big data, and AI, the use of digital twins in the industrial sector will significantly drive changes in product design, production, maintenance, and repair. Based on its advantages in models, data, and services, digital twins are becoming a key technology for the Industrial Internet. Simultaneously, the Industrial Internet is serving as an incubator for expanding the application scenarios of digital twin technology, gradually extending from manufacturing to more broader industrial internet spaces.
However, digital twin technology is still in its early stages globally. Only a few large companies, such as General Electric, Alibaba, and Microsoft, have attempted to use it to transform equipment and processes in specific areas and processes. Currently, China's digitalization level in industries and cities remains relatively weak, lacking the data foundation and technical support needed to build digital twins. For enterprises, the main theme at this stage of development will be to gradually promote digital transformation and streamline data flow between business and management levels.
