# Digital Twin and Reinforcement Learning-Based Resilient Production Control for Micro Smart Factory
## 5 Industrial Case Study
### Discussion  
The three experiments illustrate the improved performance of the proposed method over the existing heuristics rule described in Equation (7), which is similar in concept to the LPT rule--the state-of-the-art heuristics rule for dispatching. Thus, the experiment can be projected as an experiment between the proposed method and the state-of-the-art heuristics rule that was modified for appropriate application in MSF. In addition, the three experiments verify and validate the three aspects discussed below. The verification is performed based on Plant Simulation, which is the selected DT engine in this study.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Proposed Method**} & \multicolumn{3}{c}{**Existing Heuristics**} \\ \hline
**Case No.** & \(C_{max}\) & \(\sigma(c_{i})\) & \(k\) & \(C_{max}\) & \(\sigma(c_{i})\) & \(k\) \\ \hline
1 & 37.152 & 0.198 & 6 & 38.075 & 0.211 & 7 \\
2 & 36.613 & 0.200 & 6 & 37.810 & 0.215 & 6 \\
3 & 36.492 & 0.187 & 5 & 37.809 & 0.193 & 6 \\
4 & 37.139 & 0.196 & 7 & 38.428 & 0.218 & 5 \\
5 & 37.172 & 0.199 & 4 & 38.184 & 0.231 & 7 \\ \hline Average & 36.914 & 0.196 & 5.6 & 38.061 & 0.214 & 6.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Result of the experiment for resilience in type phase (unit: hour).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Proposed Method**} & \multicolumn{3}{c}{**Existing Heuristics**} \\ \hline
**Type** & \(C_{max}\) & \(\sigma(c_{i})\) & \(k\) & \(C_{max}\) & \(\sigma(c_{i})\) & \(k\) \\ \hline Current & 37.152 & 0.198 & 6 & 38.075 & 0.211 & 7 \\ Polishing & 34.521 & 0.187 & 8 & 35.877 & 0.200 & 9 \\ Fumigation & 33.152 & 0.176 & 8 & 33.962 & 0.188 & 13 \\ Assy. No. 1 & 35.645 & 0.210 & 9 & 36.423 & 0.226 & 8 \\ Assy. No. 2 & 36.329 & 0.215 & 6 & 37.154 & 0.229 & 6 \\ \hline Average & 35.360 & 0.985 & 7.4 & 36.298 & 0.211 & 8.6 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Result of the experiment for the structure of MMS perspective (unit: hour).  
Additionally, the three validation aspects are considered from the perspectives of when the configuration of MSF is restructured; when the type phase of work center-level value stream requires resilience for preventing the degradation of performance indicators; and when the instance phase of work center-level value stream also requires the resilience.  
In most cases of each experiment and as shown in Table 6, the makespan \(C_{max}\) shows an evident improvement because all cases show an improvement in this indicator. To enable the affordable delivery of personalized products to end-customers, the improvement of the lead time perspective supports this aspect. In addition, the proposed method also shows a relatively constant cycle time to balance the workload of inspection and packaging processes. The last processes that have the appointed capacity can enhance the process and systematic efficiency by balancing the workload. Moreover, the robustness of the proposed method is demonstrated when the resource instance is added as a characteristic of MMS, and the _dynamic response_ is performed to prevent performance hurdles because of the events.