Digital twin refers to constructing an identical entity in the digital world through digital means for objects in the physical world, thereby realizing the understanding, analysis and optimization of the physical entity. Since 2019, there have been two hotly-hyped concepts in A-shares. One is edge computing and the other is digital twins. Especially when the Boeing 737 MAX8 aircraft suffered a serious crash and Notre Dame Cathedral in Paris, France was burned down, the discussion around digital twin technology became even more intense. It's a climax. Among the top ten strategic technology trends released by Gartner in 2019, digital twins are also included. IDC predicts that by 2020, the world's top 600 companies will use digital twins to provide product innovation. MarketsandMarkets predicts that the digital twin market will reach US$15.7 billion by 2023, growing at a compound annual growth rate of 38%. Digital twins have broad prospects for future development.
Digital twin development, smart manufacturing, blockchain development
Digital twin drives smart manufacturing
The advantages of digital twins in manufacturing are significant. There is a saying in the industry of "1% revolution in the industrial field", that is, global industrial production efficiency increases by 1% and costs are reduced by 30 billion. According to Gartner: “By 2021, half of large industrial companies will use digital twins, making these organizations 10% more effective.”
Digital twins map various attributes of physical equipment into virtual space through design tools, simulation tools, the Internet of Things, etc., forming a detachable, copyable, modifyable, and deletable digital image, which improves the operator's understanding of physical equipment. understanding of entities. This will make production more convenient and shorten the production cycle. Of course, digital twins can calculate and summarize some immeasurable indicators through real-time understanding of target sensing data, prediction and analysis of empirical models, and machine learning, and can also greatly improve the understanding and control of mechanical equipment and processes. and predictions.
Therefore, digital twins can improve the efficiency of design, operation, control and management by enabling deep understanding, correct reasoning and precise operation of objects in physical and logical spaces.
Product-oriented digital twin applications focus on product life cycle optimization. For example, AFRL cooperates with NASA to build an F-15 digital twin