## 5 Conclusions
The minor deviations observed (5.3%) were mainly associated with human variability during manual insertion tasks, short-term machine disturbances, and micro-delays not modeled in the simulation to preserve model universality. To further reinforce the credibility of the model, scenario-based tests and sensitivity analyses were conducted. Known disturbances, such as temporary workstation idleness or shifts in the timing of pallet returns, were introduced in both the real process and the model. The system's reaction in terms of buffer buildup, decreased throughput, and reallocation of resources showed high consistency, confirming the model's predictive capability. In addition to numerical comparisons, visual validation was employed. Engineers familiar with the production process were invited to review the animated simulation. Thanks to FlexSim's detailed 3D modeling, the flow of materials, worker actions, and machine operations could be visually confirmed as accurate. The qualitative feedback from these experts supported the conclusion that the model realistically and reliably represented the selective soldering process. With such a robust validation foundation, the model became not only an analytical tool but also a reliable forecasting and decision support environment. It can now be used to assess the consequences of layout changes, pallet number variations, and process sequencing, without disrupting the actual production line. The summary of benefits presented in this work clearly indicates that simulation models are indispensable tools in production process optimization. They enable detailed replication of real systems in a virtual environment, allowing for in-depth analysis and testing of various scenarios without risking disruption of ongoing operations. Through simulation, bottlenecks can be precisely identified, material flows improved, resources efficiently utilized, and the best operational strategies selected, thereby supporting the development and competitiveness of the enterprise. FlexSim stands out as an advanced discrete-event simulation tool offering a wide range of features that support process modeling and analysis. Its ability to import data from Excel, AutoCAD, and SketchUp significantly accelerates model building and integration with existing documentation. Built-in SQL support simplifies data management, while the Process Flow panel allows intuitive creation of process logic using both prebuilt blocks and custom solutions. In summary, simulation is the key to understanding and improving complex processes, enabling informed decision-making within a safe virtual environment, where risk becomes a learning tool and optimization forms the foundation of innovation. Conceptualization, M.D. and M.K. ; methodology, M.D. and M.K. ; software, M.D. and M.K. ; formal analysis, M.D. and M.K. ; investigation, M.D. and M.K. ; resources, M.D. and M.K. ; data curation, M.D. and M.K. ; writing--original draft preparation, M.D. and M.K. ; writing--review and editing, M.D. and M.K. ; visualization, M.D. and M.K. ; supervision, M.D. and M.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s). The authors declare no conflicts of interest.