With the arrival of the Industry 4.0 era, intelligent manufacturing has become an important direction for the transformation and upgrading of the manufacturing industry. And digital twin technology as an important support for intelligent manufacturing, its application prospects are becoming more and more extensive. As an academician of the Chinese Academy of Engineering, Hu Jianguan has made important contributions to the research and application of digital twin technology. In this paper, we will introduce the concept of digital twin technology, application scenarios, operation steps and other aspects in detail.
I. The Concept of Digital Twin Technology
Digital twin technology is a technology that combines physical entities and digital models, modeling and simulating the entities through digitalization in order to realize the full life cycle monitoring and management of the entities. Digital twin technology includes three main aspects: digital modeling, digital simulation and digital services.
Digital modeling refers to the digitization of physical entities through 3D scanning and other means to establish a digital twin model. Digital simulation refers to simulation and analysis through the digital twin model in order to realize the full life cycle monitoring and management of the entity. Digital service refers to the realization of services such as remote monitoring, fault diagnosis and predictive maintenance of entities through digital twin technology.
II. Application Scenarios of Digital Twin Technology
Digital twin technology can be applied in various fields, including aerospace, automotive, mechanical manufacturing, construction, medical and so on. The following is an example of the application scenarios of digital twin technology in mechanical manufacturing.
1. Product design stage
In the product design stage, digital twin technology can realize the full life cycle design and simulation analysis of products through digital modeling and digital simulation. Through digital modeling, the digital twin model of a product can be quickly established and various simulation analyses can be performed, such as structural strength, fatigue life, fluid dynamics and so on. Through digital simulation, the performance and reliability of the product can be quickly evaluated and the design scheme can be optimized.
2. Manufacturing Process Stage
In the manufacturing process stage, digital twin technology can realize remote monitoring and troubleshooting of the manufacturing process through digital services. Through digital services, various parameters in the manufacturing process, such as temperature, pressure, vibration, etc., as well as the operating status of equipment can be monitored in real time. When a fault occurs, remote diagnosis and repair can be carried out through the digitalization service to improve the operational efficiency and reliability of the equipment.
3. Product Operation Stage
In the product operation stage, digital twin technology can realize remote monitoring and predictive maintenance of products through digital services. Through digital services, the operational status of the product and various parameters, such as temperature, pressure, vibration, etc., can be monitored in real time. When a fault occurs, remote diagnosis and maintenance can be carried out through digital services to improve product reliability and service quality.
Three, the operating steps of digital twin technology
The operating steps of digital twin technology mainly include digital modeling, digital simulation and digital services. The following digital modeling as an example, introduces the operational steps of digital twin technology.
1. Preparation
Before digital modeling, it is necessary to prepare the relevant equipment and software tools, such as 3D scanners, CAD software, modeling software and so on. At the same time, the process and standards of digital modeling need to be developed to ensure the accuracy and reliability of the modeling.
2. Digital Modeling
Digital modeling refers to the digitization of physical entities through 3D scanning and other means to establish a digital twin model. The process of digital modeling includes the following steps:
(1) Preparation of physical entities: the physical entities to be digitally modeled are prepared, such as cleaning and positioning.
(2) Perform 3D scanning: the physical entities are scanned using a 3D scanner to generate point cloud data.
(3) Point cloud processing: The point cloud data is processed, such as de-noising, alignment, etc., to generate a 3D model.
(4) Establishment of digital twin model: using CAD software or modeling software, the 3D model is converted into a digital twin model.
3. Digital Simulation
Digital simulation refers to the simulation and analysis through the digital twin model in order to realize the full life cycle monitoring and management of the entity. The process of digital simulation includes the following steps:
(1) Establish simulation model: according to the digital twin model, establish the corresponding simulation model.
(2) Selection of simulation tools: Select the corresponding simulation tools, such as finite element analysis software, fluid mechanics simulation software, etc..
(3) Perform simulation analysis: use the simulation tool to perform various simulation analyses on the digital twin model, such as structural strength, fatigue life, hydrodynamics and so on.
4. Digital service
Digital service refers to the realization of services such as remote monitoring, fault diagnosis and predictive maintenance of entities through digital twin technology. The process of digital services includes the following steps:
(1) Device connection: connect the devices that need to be remotely monitored and maintained, and establish a communication channel between the devices and the digital twin platform.
(2) Data Acquisition: through sensors and other devices, real-time data acquisition is performed on the equipment, such as temperature, pressure, vibration and so on.
(3) Data transmission: the collected data is transmitted to the digital twin platform through the communication channel.
(4) Data analysis: the transmitted data is analyzed for services such as fault diagnosis and predictive maintenance.