# Application of Modeling and Simulation in a Self-Reprogrammable Prototype of a Manufacturing System
## 5 Test and Results
Using this dataset, the equation described earlier is applied to determine the optimal conveyor speed necessary to meet the specified production targets. The computed speed values are presented in the final column, named \"Speed\". The data presented in Table 2 indicate that conveyor speed adjustments were required at three specific points during the process, occurring in cycles 3, 5, and 8. In the first two instances, these adjustments were necessitated by failures in the loading process, which resulted in the conveyor system transporting only two parts per cycle. In cycle 8, a failure at the intermediate workstation caused a 12 s delay in the cycle. In each of these cases, the simulation model processed the real-time data, activated the control trigger, and computed the optimal speed adjustment to mitigate the issue. The conveyor, operating autonomously, implemented the new speed parameters to adhere to the predefined production time of 550 s. As a result of these corrective measures, the total duration required to transport all 40 parts was 549.4 s. Due to loading failures in cycles 3 and 5, the process required 11 work cycles instead of the initially planned 10. Figure 7 illustrates the changes in conveyor speed across work cycles. The data clearly demonstrates that upon detecting a failure, the system dynamically adjusts the speed to compensate for lost time and maintain production efficiency. The data presented in Table 3 indicate that conveyor speed adjustments were required at two specific points during the process, occurring in cycles 2 and 6. In the first instances, the adjustment was necessitated by failures in the loading process, which resulted in the  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{5}{c}{**TEST 3—DATA**} \\ \hline \multirow{2}{*}{**Cycles**} & **Total Parts** & **Increment** & \multirow{2}{*}{**Cycle Time (s)**} & **Total Time (s)** & **Available** & \multirow{2}{*}{**Speed (cm/s)**} \\  & **(Units)** & **(Units)** & & & & \\ \hline Cycle 0 & 0 & 0 & 0 & 0 & 300 & 0 \\ Cycle 1 & 4 & 4 & 52.8 & 52.8 & 247.20 & 13 \\ Cycle 2 & 8 & 4 & 52.5 & 105.3 & 194.70 & 13.1 \\ Cycle 3 & 12 & 4 & 64.1 & 16  
conveyor system not transporting any part in cycle 2. In cycle 6, a failure at the intermediate workstation caused a 14 s delay in the cycle approximately. The simulation model was activated to make speed adjustment, consequently, mitigate the issue. The conveyor, operating autonomously, implemented the new speed parameters to adhere to the predefined production time of 600 s. As a result of these corrective measures, the total duration required to transport all 40 parts was 600.9 s, in addition, one more cycle was required. Figure 8 illustrates the changes in conveyor speed that occurred on cycles 3 and 7 across work cycles. The data presented in Table 4 indicates that conveyor speed adjustments were required when there occurred a failure on cycle 3, in that situation cycle time delay approximately 11 s. The adjustment was necessitated to keep the time process goal, 300 s to transport 24 parts. Figure 9 illustrates the changes in conveyor speed that occurred on cycle 3 across work cycles. Figure 8: Monitoring speed changes during the time in test 2. Figure 9: Monitoring speed changes during the time in test 3. Another test was conducted to analyze the conveyor speed when the cycle time is altered. In this test, the data from the planned cycle time (IT) and the observed cycle times (T1, T2, and T3) were compared, along with the Corrected Cycle Time (TSA). The charts in Figure 10 illustrate the variations in the test parameters, where chart (A) shows the time variation in seconds, and chart (B) depicts the percentage variation in time. The orange line (Delta IT% and Delta IT) represents the time reference for each of the four cycles analyzed. The blue, yellow, and red lines show the data collected without optimization. The green lines (Delta TSA% and Delta TSA) correspond to the cycles where optimization was applied.