20.500.12556/DKUM-93042 Optimizacija procesnih parametrov pri postopku brizganja plastike magistrsko delo Optimization of process parameters in the plastic injection molding process Optimizacija parametrov pri injekcijskem brizganju plastike je eden od najpomembnejših korakov pri načrtovanju proizvodnega procesa injekcijskega brizganja s katerim zagotovimo boljšo kakovost izdelka in stabilnost proizvodnega procesa. Kot študijski primer je bilo izbrano ohišje za Raspberry Pi, ki predstavlja tankostenski izdelek, primeren za optimizacijo v programskem okolju Autodesk Moldflow Insight 2023. Teoretični del opisuje osnovne principe tehnologije brizganja ter vpliv ključnih procesnih parametrov na najpogostejše napake pri izvedbi procesa brizganja. V eksperimentalnem delu je bila izvedena vrsta numeričnih optimizacij s katerimi so analizirani vplivni parametri in njihov vpliv na končni izdelek. Z uporabo statistične metode DOE (Design of Experiments) smo preučili kombinacije, ki vodijo k zmanjšanju napak, krajšem ciklu in večji ponovljivosti procesa. Rezultati kažejo, da je z optimizacijo mogoče doseči bistvene izboljšave kakovosti izdelka ter skrajšanja časa cikla brez sprememb geometrije izdelka. The optimization of parameters in plastic injection molding is one of the most important steps in designing a manufacturing process, as it ensures improved product quality and production stability. The Raspberry Pi enclosure was selected as the case study, representing a thin-walled product suitable for optimization using the Autodesk Moldflow Insight 2023 software environment. The theoretical part describes the basic principles of injection molding technology and the influence of key process parameters on the most common defects occurring during the molding process. In the experimental part, a series of numerical optimizations were carried out to analyse the influential parameters and their impact on the final product. Using the statistical DOE (Design of Experiments) method, parameter combinations were studied that lead to reduced defects, shorter cycle times, and greater process repeatability. The results show that optimization can achieve significant improvements in product quality and reductions in cycle time without changing the product geometry. injekcijsko brizganje optimizacija procesa Moldflow Insight Raspberry Pi ohišje numerična simulacija kakovost izdelka DOE injection molding process optimization Moldflow Insight Raspberry Pi enclosure numerical simulation product quality DOE true true false [D. Bistrović] Slovenski jezik Angleški jezik Magistrsko delo/naloga 2025-06-02 15:16:37 2025-06-27 08:48:04 2025-07-04 03:09:04 0000-00-00 00:00:00 2025 0 Maribor 0 Maribor 1 spletni vir (1 datoteka PDF (X, 84 f.)) 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 678.027.74-048.33(043.2) 241220099 MAG_Bistrovic_Dominik_2025.pdf MAG_Bistrovic_Dominik_2025.pdf 1 64FFB5A1C28551D93B4FB46DAFE8323D 89caa4965be250f3bb93f0ca2c3681bd4c392124ffc70331a48b910a2ac195dd dc25fb10-5140-11f0-ab14-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=192714 Fakulteta za strojništvo 0 0 0