## 3 Results
### Identified Bottlenecks and Insights  
The analysis centered around the company's use of micro-batches, which represent small, order-specific production batches organized around the output of the plotter. Each micro-batch begins when the operator aggregates a group of print jobs and generates a roll-specific print file [25]. This event initiates a tightly coupled sequence: white fabric components are prepared, aligned with the roll content, and stacked for pressing. The press then operates at a fixed technological speed, processing each roll according to predefined thermal and pressure settings. The micro-batch ends once all units are pressed and transferred to quality control. Early simulation scenarios revealed that this structure, although efficient in principle, relies heavily on precise coordination between workstations [26]. Plotter throughput sets the rhythm, while upstream and downstream stations (preparation and press) must synchronize their activities to avoid idle time or bottlenecks. In particular, white detail preparation exhibited delays in aligning material readiness with roll completion, resulting in repeated idle periods at the press. This issue was validated through real-time measurements. The press workstation exhibited stable operating parameters; however, clusters of idle states often coincided with late material delivery. Conversely, the plotter experienced workload spikes due to variable job grouping and the formation of ad hoc micro-batches. These variations amplified the inconsistency in the downstream flow. To analyze the issue holistically, simulation results were compared with real production data collected through the DIMUSA platform [27]. This cross-validation helped confirm that the observed performance gaps stemmed not from individual workstation inefficiencies but from structural misalignments in micro-batch sequencing. The cluster-based visualization made these patterns explicit, supporting root-cause discussions during daily meetings with team leaders. Overall, the findings emphasized the importance of digital support for batch logic and material readiness, particularly in environments characterized by short-run variability and manual task transitions [28]. The micro-batch logic, described below in  
Figure 7: Availability vs. performance plot of clustered workstation data based on virtual factory simulation output from October 2024.  
Figure 8, illustrates the tightly coupled flow initiated by the plotter and concluded at the quality control step, underpinning the coordination issues discussed in this section.  
The micro-batch process begins with aggregated order data, which is grouped at the plotter workstation into printable roll files. Each roll considers the printing material and thermal press parameters. Based on the roll content, fabric pieces are pre-cut and stacked in sequence to align with the upcoming press cycle. The thermal press applies heat and pressure to transfer the print onto each aligned fabric layer. The process ends when the printed components are transferred to quality control. This structure ensures a clear production rhythm but also introduces synchronization dependencies between the plotter, cutting, and pressing operations.