## 3 Model Establishment
### The Method of Modelling Process
The lack of synchronization among workstations led to waiting times, as some stations had to wait for previous tasks to be completed. This reduced overall production efficiency. Furthermore, delays in material delivery prevented some stations from proceeding as planned, which further contributed to underutilization. Future research should focus on improving AGV scheduling, strengthening material supply chain management, and implementing more balanced task distribution to enhance workstation utilization and increase production efficiency. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & **Assembly** & **Assembly** & **Assembly** & **Test** & **Pack** \\  & & **Station 1** & **Station 2** & **Station 3** & & \\ \hline \multirow{3}{*}{Working proportion} & Original & 5.92\% & 1.66\% & 1.67\% & 1.68\% & 1.67\% \\  & After optimization & 42.46\% & 28.07\% & 28.07\% & 27.06\% & 26.74\% \\  & Improved proportion & 36.54\% & 26.41\% & 26.40\% & 25.38\% & 25.07\% \\ \hline \multirow{3}{*}{Waiting proportion} & Original & 94.08\% & 98.34\% & 98.33\% & 98.32\% & 98.33\% \\  & After optimization & 57.54\% & 71.93\% & 71.93\% & 72.94\% & 73.26\% \\  & Improved proportion & 36.54\% & 26.41\% & 26.40\% & 25.38\% & 25.07\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of data before and after optimization of five stations. ### Practical Application and Impact

The AGV scheduling optimization method proposed in this study holds substantial practical value, particularly in complex production environments such as complex product assembly workshops. These settings, especially when dealing with large and heavy components like cabin sections, often suffer from inefficiencies, resource waste, and transportation bottlenecks due to reliance on manual scheduling and transport. The proposed method enhances the precision of AGV scheduling, shortens transportation time, and improves workstation utilization, thereby significantly boosting overall production efficiency. Efficient AGV scheduling and path planning are critical for ensuring smooth operations during the transportation of large aerospace components. For instance, in the production of cabin sections, AGVs are tasked with moving bulky and heavy parts between various processing stages. An optimized scheduling scheme minimizes equipment idleness and resource waste, eliminates bottlenecks associated with traditional transport methods, and ensures seamless task coordination. Although this study focuses primarily on the aerospace sector, the proposed optimization method is equally applicable to other manufacturing industries, such as automotive and electronics assembly. In these fields, similar AGV scheduling strategies can significantly reduce production costs and enhance logistics efficiency. To apply this method in practice, enterprises can construct simulation models of their workshops, configure key operational parameters, and perform scheduling optimization to achieve more flexible and efficient production planning. ## 5 Conclusions

This study introduces an innovative approach to addressing inefficiencies and operational complexities in complex product assembly workshops by integrating AGVs with Discrete Event Simulation (DES). By tailoring AGV deployment to the stringent precision and coordination requirements of aerospace manufacturing, the proposed method enables optimized workstation configurations and real-time production monitoring, significantly improving overall operational efficiency. Notably, the utilization rate of workstations increased from less than 6% to over 28%, while waiting time was reduced from 94% to below 74%. These results demonstrate the considerable advantages of combining AGVs with advanced simulation techniques in industries that demand high levels of precision, flexibility, and responsiveness. Future research could focus on optimizing AGV scheduling, enhancing material supply chain management, and improving task allocation strategies to increase workstation utilization and overall production efficiency.