Szczegóły publikacji
Opis bibliograficzny
Application of computer simulation to evaluate performance parameters of the selective soldering process / Maciej Dominik, Marek KĘSEK // Applied Sciences (Basel) [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2076-3417 . — 2025 — vol. 15 iss. 15 art. no. 8649, s. 1–21. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 20–21, Abstr. — Publikacja dostępna online od: 2025-08-05
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 162043 |
|---|---|
| Data dodania do BaDAP | 2025-09-05 |
| Tekst źródłowy | URL |
| DOI | 10.3390/app15158649 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Applied Sciences (Basel) |
Abstract
The growing complexity of production systems in the technology sector demands advanced tools to ensure efficiency, flexibility, and cost-effectiveness. This study presents the development of a simulation model for a selective soldering line at a technology manufacturing company in Poland, created during an engineering internship. Using FlexSim 24.2 software, the real production process was replicated, including input/output queues, manual insertion (MI) stations, soldering machines, and quality control points. Special emphasis was placed on implementing dynamic process logic via ProcessFlow, enabling detailed modeling of token flow and system behavior. Through experimentation, various configurations were tested to optimize process time and the number of soldering pallets in circulation. The results revealed that reducing pallets from 12 to 8 maintains process continuity while offering cost savings without impacting performance. An intuitive operator panel was also developed, allowing users to adjust parameters and monitor outcomes in real time. The project demonstrates that simulation not only supports operational decision-making and resource planning but also enhances interdisciplinary communication by visually conveying complex workflows. Ultimately, the study confirms that simulation modeling is a powerful and adaptable approach to production optimization, contributing to long-term strategic improvements and innovation in technologically advanced manufacturing environments.
