"Digital twins" and modeling simulation technology have been called the next wave of smart manufacturing, and Industry 4.0 also requires that digital models must first appear in order to interact with each other and enhance each other.
What is digital twins?
"Digital Twin" refers to the digital copying of a physical object, simulating the behavior of the object in the real environment, and virtual simulation of the product, the manufacturing process and the entire factory, thereby improving the production efficiency of the manufacturing company's product development and manufacturing. .
All "products" were originally a vague concept in the human brain. Without the help of a digital model, to create a product or a set of production processes, it will inevitably undergo multiple iterations of design, sometimes just to verify the product. A certain size, assembly relationship between components, and a certain part of the process, have to create a lot of intermediate products or redesign process (called proofing), which takes a lot of time, money and manpower. Design techniques using digital models (often referred to as CAD technology, or digital aided design) create components and products and processes from scratch in a virtual three-dimensional digital space. In the virtual three-dimensional space, it is easy to modify each dimension and assembly relationship of components and products, so that the verification of product geometry, the verification of assembly feasibility, and the practicability of the process are much simpler, so it can be large. The amplitude reduces the number of manufacturing, time, and cost of the physical prototype during the iterative process. In addition, specialized circuit CAD design techniques can be used to design circuits in a three-dimensional digital space based on the principles of the circuit and the device, as well as virtual verification and iterative design. It also significantly reduces the cost of manufacturing physical prototypes. This is why digital models must be earlier than physical physical products. In fact, there are many digital models that represent the various stages of product iteration before the final product is manufactured. These models, or some of them, may still be adopted by future models or product lines, which is an added benefit of the digital model.
Modeling and Simulation of "Before and Present"
Modeling and simulation was originally derived from the digital algorithms written in computer languages ​​from the 1960s to the 1970s. It was simply used to calculate specific physical phenomena and solve design problems. In the next two decades, with the popularity of workstations and microcomputers. With the improvement of computing power, the application of simulation technology has gradually spread to various disciplines and different levels; and it will not stay at the design stage, and is expanding to the full life cycle of products and systems, forming a "digital twin" that is inseparable from the entity. As simulation can provide seamless assistance and optimization during the product life cycle, it will become one of the core functions of the manufacturing system. The future smart factory is model-based system engineering or model-based manufacturing, software-defined products, determining the rise and fall of the enterprise, and simulation technology. The golden age of the key components of the manufacturing system has only just begun. Gartner predicts that by 2021, 50% of the world's largest industrial companies will use digital twins, increasing the efficiency of these organizations by 10%, especially in manufacturing and engineering companies, if they want to stay ahead of the competition, Need to consider implementing digital twins.
Manufacturing is currently the most commonly used industry for digital twins. Providing quality and quantity to customers on time is critical to manufacturing companies. If machines do not work together and work at the right capacity, it will affect employees, production, and deliverability. And end-customer satisfaction; with real-time monitoring, testing without interruption, and the ability to get more information from millions of digital locations collected in the facility, digital twins make manufacturing companies smarter.
In a case study at Deloitte, an industrial manufacturing company decided to use digital twins to solve its problems at the site, thereby addressing maintenance costs and delayed customer delivery. Manufacturers collect equipment and product data being produced to study the assembly process and its relationship to product quality. As a result, the project was able to identify inefficiencies and optimize the assembly process, reducing rework rates by 15% to 20%.
Domestic status of digital twins
The first to introduce the concept of "digital twins" in the market is Siemens, the model-based virtual enterprise and the "digital twins" of real-world enterprises based on automation technology, including "product digital twins", "production process digital twins" And "device digital twins", three levels are highly integrated into a unified data model, and through digitalization to help enterprises integrate horizontal and vertical value chains, provide industrial ecosystem remodeling and achieve "Industry 4.0" bottom-up A practical road.
The introduction of digital twins in China for only a few years is currently in the initial exploration and practice. There is still a long way to go before it can be widely used. At present, digital twin technology faces many problems, which can be divided into three categories: Simulation, high-fidelity simulation modeling is the key to constructing a digital twin system. Digital twins are used as physical entities in the super-realistic dynamic model of digital space. High-precision, multi-physics modeling, high-fidelity response of product virtual models Simulation and so on are the primary technical problems solved. The second is data collection, because the application of digital hygiene technology is based on massive data, and is based on total factor, full life cycle data, and the advanced sensor technology, adaptive sensing, precise control and execution technology involved in these data. The problem is urgently needed. Third, real-time monitoring and health prediction technology has yet to be improved. Real-time and prediction are the core elements of digital hygiene. On the one hand, the data dynamics of physical products are reflected in the digital twinning system in real time. On the other hand, digital twinning is based on perceptual big data. Analyze decision-making, and then control physical products, which are inseparable from the corresponding high-real-time data interaction, high confidence simulation prediction, super computing power and other technical capabilities. In addition, the new design verification method still needs to be further explored, so that the experimental results of the physical model are more accurate and closer to the real working conditions, providing reliable data support for the derivation of digital twins.
At present, China's manufacturing industry is in a critical period of transformation and upgrading. Through the deep integration of the Internet of Things, big data, artificial intelligence and the real economy, China's manufacturing competitiveness has been greatly improved. In the future, digital twins can also be combined with IoT data collection, big data processing and artificial intelligence modeling analysis to achieve the diagnosis of past problems, the assessment of current status and the prediction of future trends, and give analysis results to simulate various possibilities. Sexuality provides more comprehensive decision support.
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