## 6 Case Validation and Discussion
### Application of the Digital Twin System in Workshop  
For testing and validation, the proposed digital twin system architecture in this paper is implemented at a Chinese ocean engineering manufacturer. Each business module in the system may function both independently and efficiently together to assist in the fulfillment of the digital twin service via the system's adoption of a micro-service architecture. The service middleware and management backend use Java and Oracle, the system front-end uses Vue.js technology, and the visualization board is finished using Unity 3, and other open-source board technology. As indicated in Figure 15, it completes the creation of 5 modules and 33 functions. The system function module is designed to complete data management in phases of the ocean engineering construction process, integrate corresponding business data according to design, manufacturing, and basic data, provide prediction and optimization services, and eventually provide a visualization board to fulfill decision support.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline  &
\begin{tabular}{c} **Size** \\ **(\(n\times m\))** \\ \end{tabular} & **GAT-DRL** & **FIFO** & **SPT** & **LPT** & **MWKR** & **GA** \\ \hline \(c_{max}\) & & 1448 & 1513 & 1546 & 1547 & 1489 & 1433 \\ Time & \(15\times 15\) & 1.11 & 0.60 & 0.74 & 0.71 & 0.71 & 46.17 \\ Gap & & 3.14\% & 5.58\% & 7.89\% & 7.98\% & 4.31\% & 0.56\% \\ \hline \(c_{max}\) & & 1646 & 1778 & 1814 & 1775 & 1677 & 1702 \\ Time & \(20\times 15\) & 1.46 & 0.81 & 0.99 & 0.93 & 0.96 & 60.66 \\ Gap & & 2.52\% & 8.00\% & 10.31\% & 7.82\% & 3.55\% & 3.37\% \\ \hline \(c_{max}\) & & 2189 & 2330 & 2419 & 2379 & 2216 & 2275 \\ Time & \(30\times 15\) & 2.31 & 1.48 & 1.87 & 1.79 & 1.78 & 96.20 \\ Gap & & 3.60\% & 7.55\% & 10.83\% & 9.12\% & 3.69\% & 3.91\% \\ \hline \(c_{max}\) & & 1933 & 2065 & 2067 & 2128 & 2005 & 2012 \\ Time & \(20\times 20\) & 1.98 & 1.09 & 1.31 & 1.18 & 1.26 & 82.29 \\ Gap & & 2.17\% & 6.80\% & 6.93\% & 10.09\% & 3.94\% & 4.06\% \\ \hline \(c_{max}\) & & 2403 & 2549 & 2619 & 2604 & 2479 & 2580 \\ Time & \(30\times 20\) & 3.57 & 1.97 & 2.46 & 2.31 & 2.34 & 148.80 \\ Gap & & 3.70\% & 6.09\% & 8.99\% & 8.36\% & 4.61\% & 7.34\% \\ \hline \(c_{max}\) & & 3338 & 3504 & 3571 & 3501 & 3368 & 3754 \\ Time & \(50\times 20\) & 9.09 & 3.14 & 4.23 & 3.86 & 3.89 & 378.77 \\ Gap & & 4.58\% & 6.32\% & 7.02\% & 5.25\% & 4.00\% & 12.46\% \\ \hline \(c_{max}\) & & 5845 & 6052 & 6139 & 6093 & 5840 & 6374 \\ Time & \(100\times 20\) & 43.42 & 13.20 & 21.14 & 19.14 & 19.97 & 1808.81 \\ Gap & & 3.04\% & 4.81\% & 5.12\% & 4.82\% & 2.95\% & 9.14\% \\ \hline \(c_{max}\) & & 6782 & 6934 & 7117 & 7004 & 6811 & 6845 \\ Time & \(100\times 12\) & 25.76 & 7.93 & 12.66 & 11.52 & 12.04 & 1073.09 \\ Gap & & 6.75\% & 7.72\% & 9.20\% & 6.09\% & 5.88\% & 1.56\% \\ \hline \end{tabular}
\end{table}
Table 3: Comparison of models’ performance in different scale data.  
By contrasting the DT system with the in-service MES in the block assembly and welding workshop, system validation of multiple project construction scheduling has been carried out. The test results are listed in Table 4. According to the findings, the DT system's scheduling function compared to the MES can be completed in 5.08% less time for the total duration, and calculation speed can be increased by 16.30%. The visual interface of this system not only makes it convenient to monitor the job plan and progress in the workshop,  
Figure 14: Relative gaps of algorithm results for different size datasets.  
Figure 15: Application of the DT system for OE intelligent workshop.  
but it also emphasizes the optimization of the data-driven job execution process and makes use of the five-dimensional logic model in production management.