## 4 Construction of Digital Twin Production Line  
### Construction Process of Digital Twin Production Line  
The specific method and flow of digital twin production line construction are shown in Figure 5. By following a comprehensive process that includes data collection, model establishment, validation, and optimization, a digital twin model is created, accurately mirroring the actual production line within a virtual environment. This model offers powerful tools for the design and optimization of intelligent production lines, as it can simulate and predict the actual operation of the production line in real time, allowing for continuous improvement and efficiency gains. This is exemplified by the application of digital twin technology at the equipment level, which facilitates real-time monitoring and simulation, as well as the specific patent for a digital twin-based production line data mapping and integration system, which enhances the management and optimization of production line processes, as detailed below:(1) 3D digital model creation and importation: Utilizing cutting-edge 3D modeling tools such as CATIA and UG to meticulously create 3D models that accurately represent essential equipment, including industrial robots, CNC machining centers, grinding machines, testing devices, sorters, storage systems, and integrated control systems. By converting these models into the.robp format, they become compatible with digital twin software. This compatibility facilitates the successful importation and precise virtual reproduction of the production line within the digital twin environment. Establishing a robust foundation for virtual debugging and digital twin modeling is crucial, as it enables the creation of accurate virtual counterparts of physical entities. This process significantly enhances the monitoring, simulation, forecasting, and improvement of real-world systems. (2) Definition and application of sensors: Sensors, as essential detection devices in industrial automation, are adept at converting measured data into electrical signals or other output formats. This transformation facilitates the transmission, processing, storage, display, recording, and control of information, thereby enhancing production efficiency, quality assurance, and safety monitoring. They play a crucial role in industrial automation and are utilized across various sectors, including manufacturing, logistics, healthcare, and environmental monitoring. Advancements in technology, such as miniaturization, digitization, and the integration of artificial intelligence, have significantly improved the functionality and efficiency of sensors. In actual production lines, sensors monitor photoelectric signals to assess material conditions, employing signal blocks to confirm the presence of materials. Within the software system, the collision detection mechanism enhances the sensor's detection capabilities, enabling the recognition of material presence through virtual collisions between the digital twin model of the sensor and the physical model. (3) Definition of state machine: The concept of a state machine is fundamental in the definition of digital twin devices. Within the realm of digital twin software, this concept facilitates the characterization of mechanisms driven by primary actuators, such as motors and cylinders, as state machines. These state machines are predicated on two fundamental motion states: translation and rotation, which are expressed through actions such as the extension, rotation, clamping, and release of the mechanism. The operation and regulation of the state machine are primarily contingent upon trajectory points, which can be activated by custom events to ensure precise motion control. Each state is governed by the establishment of start and place variables, which function as the interface between the state  
Figure 5: Construction process of digital twin production line. machine and the external controller, responsible for initiating motion and providing state feedback.