## 6 Conclusions  
According to the complex and changeable assembly requirements for CBs, a multi-robot collaborative CBFMS is proposed. This method can realize the fully automatic manufacturing of CBS from parts loading to storage. To improve the assembly efficiency of key units in multi-robot collaborative CBFMS, the method of collaborative assembly of parts with two-arm cooperation robots is adopted. Finally, the DT system of multi-robot collaborative CBFMS is built to realize the prediction and monitoring of the production line, which can improve the intelligence level of the entire production system.  
1. Compared with the traditional semi-automatic production line, the overall assembly efficiency is increased by 22%. At the same time, this method can solve the problems of excessive rigidity and single assembly method in traditional assembly schemes.
2. Compared with the traditional single-robot system, the efficiency of two-arm cooperation robot assembly can be increased by 63%. This method can improve the whole CBFMS production rhythm and speed up the production process by improving the assembly efficiency of key units.
3. The DT system of multi-robot collaborative CBFMS can accurately and timely express each process of the production unit, including the selection of the best process of the whole system and the accurate mapping of actual production objectives. The proposed framework provides a set of reference implementation schemes for the construction of a physical workshop, which can greatly improve the production efficiency of CBs and optimize the structure of the production line.  
In the future, we hope to introduce human-machine-environment integration and DT system data prediction analysis. Robots can act quickly when they judge human behavior and environmental changes, and their efficiency will be further enhanced. At the same time, a large number of data models are analyzed by building the DT system, and the future trend is predicted by combining the AI algorithm.  
Conceptualization, L.W. and L.S.; methodology, L.W. and L.S.; software, L.W. and H.Z.; validation, L.W.; formal analysis, L.W. and L.S.; investigation, L.W. and L.S.; resources, L.S.; data curation, L.W. and H.Z.; writing--original draft preparation, L.W. and L.S.; writing--review and editing, L.W. and L.S.; visualization, L.W.; supervision, L.W.; project administration, L.S.; funding acquisition, L.W. and L.S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key R&D Project of Zhejiang Province, grant number No.2021C01046; by the Basic Industrial Science and Technology Project of Wenzhou, grant number G20210020; by the Zhejiang Xinmiao Talents Program, grant number 2022R429B048.  
**Institutional Review Board Statement:** Not applicable.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Function** & **Multi-Robot Cooperative CBFMS** & **Semi-Automatic Manufacturing Line** \\ \hline Production time of one CB (s) & 47.58 & 61 \\ Whether there is labor & no & yes \\ Whether the process can be changed & yes & no \\ Whether the process design is perfect & yes & no \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison between the traditional CBs manufacturing line and the multi-robot cooperative CBFMS.