## 1 Introduction

Table 1: The definition of digital twin by different scholars. In 2015, Professor [PERSON] and his research institute [20] jointly proposed the construction of a digital twin model in the field of modern manufacturing, which is completely different from the previous view that the digital twin was only applied in the aerospace field. [PERSON] and his research institutions [21] believe that digital twin technology can be introduced into the entire production process. At the same time, they also emphasize that digital twins should not be limited to a certain product, but should be applied to the entire modern manufacturing industry. [PERSON] and his team [22] mainly studied the assembly-oriented industrial grasping scene based on DRL and proposed a method supporting digital twins to realize the effective transmission of the DRL algorithm on physical robots. In order to overcome the limitation of smart grid (SG) to modify the physical configuration and scalability of W.R.T., [PERSON] and his team [23] established a digital twin model for the physical test bench for SG network security research. [PERSON] et al. [24], by exploring the heat transfer of metal foams, established a digital twin of thermal properties experiments using computed tomography and finite element analysis. [PERSON] et al. [25] established a predictive maintenance model of electromechanical equipment by introducing digital twin technology and proposed a method to solve the fault of electromechanical equipment. [PERSON] and [PERSON] [26] further developed analog data management for digital twin applications in order to convert analog data management methods that are only suitable for virtual product development to the product use phase. [PERSON] et al. [27] provided a digital twin framework for structural engineering that is monitored by IoT sensors and actuators and is used for laboratory-scale structural testing. [PERSON] et al. [28] developed a virtual inspection system for detecting the tolerance of standard mobile mechanical parts based on the digital twin of the coordinate measuring machine as the mirror process between the physical measurement system and the virtual measurement system. [PERSON] and [PERSON] [29] described a digital-twin original solution for material extrusion 3D printers. By using the printing host software interactively, the twin program can directly intervene in the current process to suspend printing anomalies. [PERSON] et al. [30] used a digital twin in the design, monitoring, and prediction of wind turbine performance. [PERSON] et al. [31] proposed a conceptual framework based on a digital twin, which can most reasonably determine the number of operators and the number of cars that apply automatic navigation in the product department. In addition, there is a point to note. The digital twin needs to be driven by the massive amount of data distributed across the Industrial Internet of Things (IIoT) devices, while at the same time, the devices communicate frequently with each other, which necessitates advance consideration of privacy, competition, and security issues. To solve this problem, [PERSON] et al. [32] proposed a new DT-empowered IIoT (DTEI) architecture, where the virtual models of the physical objects in the IIoT are constructed by capturing the real-time status of the base stations (BSs) and devices. Then, to improve the training model efficiency of the IIoT device, a deep reinforcement learning (DRL)-assisted FL framework was proposed. Because this article mainly studies the preliminary planning of the factory production line and the factory uses its own internal LAN; hence, there is less risk in privacy, security, and competition. It should be pointed out that this problem must be carefully considered and solved when encountering systems integrated with multiple sub-factories. The major contributions of this article are summarized as follows:  
1.