## 4 Results and Discussion
### Process Flow Efficiency  
The process flow analysis revealed:  
* Primary Flow Path: Start \(\to\) 202 \(\to\) 203 \(\to\) 204 \(\to\) 205 \(\to\) 206 \(\to\) 207 \(\to\) End
* Alternative Paths: Including cross-transitions (e.g., 202 \(\to\) 205: 729 events)
* Rework Loops: Evidence of backward transitions (e.g., 205 \(\to\) 204: 3445 events)
* System Throughput: 391,127 total events processed  
The presence of significant backward transitions, particularly from Station 205 to 204, indicates quality control issues requiring rework, contributing to the bottleneck formation in these stations. Quantitative Baseline and Bottleneck Confirmation  
The quantitative baseline metrics (Table 2) confirm the bottlenecks suggested by the qualitative analyses. The relatively long cycle times and high idle times for the Printing (Station 204) and Packaging (Station 205) units are typical constraints found at the end of the primary bottleneck segment. The integration of operational data with dynamically calculated environmental metrics (EC, CE, WG), corresponding to the execution of the Life Cycle Assessment inventory (S6) and calculation of utilization rates (S7), provides a richer baseline than traditional operational analysis alone, setting the stage for multi-objective optimization. The comprehensive analysis of the tube manufacturing process revealed significant operational insights throughout the production line. The system processed a total of \begin{table}
\begin{tabular}{l r r r r r r r r} \hline \hline \multirow{2}{*}{**Machine Type**} & \multirow{2}{*}{\begin{tabular}{c} **Cycle Time** \\ **(CT)** \\ **(s)** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Idle Time** \\ **(I)** \\ **(s)** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Throughput (TP)** \\ **(s)** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Defective** \\ **Rate (DR)** \\ \end{tabular} } & \multirow{2}{*}{\begin{tabular}{c} **Energy** \\ **Consumption** \\ **(EC)** \\ \end{tabular} } & \multirow{2}{*}{\
\begin{tabular}{c} **Carbon** \\ **(EC)** \\ \end{tabular} } & \multirow{2}{*}{
\begin{tabular}{c} **Waste** \\ **Generation** \\ **(WG)** \\ \end{tabular} } \\  & & & & & & & \\ \hline Extruder (Station 202) & 750 & 95 & 115 & 2.8 & 485 & 242.5 & 18.5 \\ Capping Machine (Station 203) & 636 & 82 & 135 & 2.3 & 520 & 260.0 & 19.8 \\ Printing Unit (Station 204) & 804 & 124 & 108 & 3.5 & 468 & 234.0 & 21.2 \\ Packaging Machine (Station 205) & 684 & 98 & 126 & 2.6 & 495 & 247.5 & 20.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Tube-making machine data. 391,127 events during the observation period, with an average cycle time of 11.7 min per event and an average throughput of 126.3 events per day, achieving an overall system efficiency of 87%. The process discovery analysis identified five critical bottleneck stations (Stations 202-205) out of nine active stations, with these bottlenecks characterized by extended operational durations exceeding 9900 h each. Station 207 emerged as the best performer with a cycle time of 9.4 min per event and the highest throughput of 159 events per day, while Station 209 showed the poorest performance with a cycle time of 16.0 min per event and the lowest throughput of 94 events per day. The bottleneck stations demonstrated moderate cycle times ranging from 10.6 to 13.4 min per event but maintained relatively consistent throughput rates between 108 and 137 events per day, suggesting their bottleneck status arose from high processing volumes rather than operational inefficiency. The process flow analysis revealed a primary production path from Start \(\to\) 202 \(\to\) 203 \(\to\) 204 \(\to\) 205 \(\to\) 206 \(\to\) 207 \(\to\) End, with significant backward transitions indicating network loops, particularly from Station 205 to 204 (3445 events).