# Enhancing Production Efficiency Through Digital Twin Simulation Scheduling
## 4 Results  
The experiments involved creating a schedule and comparing its effectiveness with that of the reference variant, which was developed in the original or conventional manner. Individual variants were created gradually during the implementation of the simulation experiments. The makespan, the time remaining until the end of the shift, and the savings were selected as key indicators for the comparison of individual variants. The value of the savings is calculated based on the internal guidelines of the company in which the system is implemented. Within the framework of the experiments performed, all schedule variants (Table 2) were feasible and acceptable. Finally, the schedule from experiment 3, with the best assessment in terms of the sanction function, was applied to production. The figure below (Figure 9) shows how the production sequence of task processing is presented in the form of a Gantt chart. As part of the creation of variant solutions for the production schedule, data on the utilization of production assets and AGVs during the simulated period were automatically collected. Figure 9 shows the resulting Gantt chart created in the simulation environment. It captures the sequence and duration of individual production operations (for example, PRESS1, PRESS2, preassembly, join, motor mounting, etc.). Each row represents a separate workplace or work operation, while the horizontal color blocks show when and for how long a given task is performed. The horizontal axis shows a time scale. The chart is used to verify whether the proposed digital twin and control algorithms can plan production more efficiently than the original or conventional methods. The graphical display shows the reduction in the total production time (makespan) and the time saved until the end of the shift, as well as the achieved economic savings (evaluated in the table with plan variants--Table 2). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{3}{*}{**Experiment/ Indicator**} & \multirow{3}{*}{**Original Plan**} & \multicolumn{3}{c}{**Simulation-Based Planning**} \\ \cline{3-6}  & & **Exp. 1** & **Exp. 2** & **Exp. 3** & **Exp. 4** \\ \cline{3-6}  & & **CR, Bottom to Top** & **CR, Top to Bottom** & **FIFO, Top to Bottom** & **FIFO, Bottom to Top** \\ \hline Start of production [hh:mm:ss] & 5:45:00 & 5:45:00 & 5:45:00 & 5:45:00 & 5:45:00 \\ \hline End of production [hh:mm:ss] & 15:45:00 & 14:08:00 & 14:09:00 & 14:03:00 & 14:04:00 \\ \hline Time remaining until end of shift [hh:mm:ss] & 0 & 1:37:00 & 1:36:00 & 1:42:00 & 1:41:00 \\ \hline Makespan [hh:mm:ss] & 10:00:00 & 8:23:00 & 8:24:00 & 8:18:00 & 8:19:00 \\ \hline Produced pcs & 223 & 223 & 223 & 223 & 223 \\ \hline Is the schedule acceptable? & Yes & Yes & Yes & Yes & Yes \\ \hline Savings [EUR] & 0 & 26,464 & 26,450 & 26,533 & 26,519 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Final variants of schedules and their evaluation. Figure 10 provides two graphical representations of capacity utilization. AGV capacity utilization (top graph)  
The vertical axis represents the percentage of the total available time (T100 = 100%). The colored segments in the columns symbolize the state of the AGV device (e.g., AF 800x)--encompassing driving, crossroads, manipulation, blocking, and waiting. At first glance, it is possible to identify which device is most utilized and where downtime occurs. Workplace capacity utilization (bottom graph)  
Each column represents one workplace (PRESS1, PRESS2, preassembly, etc.). The colored sections show the proportion of time for which a workstation is working (work), setting up (setting up), waiting (waiting), blocked (blocking), in failure (failure), stopped (stop), or in a break (break). This overview helps to easily identify possible bottlenecks or excessive proportions of unproductive time. Both graphs are used when evaluating the efficiency of the planned schedule, as they clearly show how the production flow can be improved and downtime during logistical transfers can be minimized.