研究目的
To evaluate the tool life and performance of additively manufactured photopolymer mould inserts in injection moulding under various process conditions, and to develop a thermo-mechanical model to analyze failure causes and predict deformations.
研究成果
The study successfully evaluated the tool life of AM inserts in IM, identifying mould temperature as the most influential factor on crack propagation. The developed thermo-mechanical model accurately predicted failure sites and deformations, providing insights for optimizing soft tooling processes. Higher initial insert temperatures increase failure risk due to reduced yield strength and higher thermal stresses.
研究不足
The study is limited to specific photopolymer materials and IM conditions; results may not generalize to other materials or processes. The numerical model assumes simplified thermal properties and does not account for all real-world variations, such as material degradation over multiple cycles.
1:Experimental Design and Method Selection:
A Design of Experiments (DOE) approach with a 2-level fractional factorial design was used to investigate the influence of injection moulding parameters on insert performance. A thermo-mechanical finite element model with phase change was developed in COMSOL Multiphysics to simulate thermal and mechanical behaviors.
2:Sample Selection and Data Sources:
Mould inserts were fabricated using digital light processing (DLP) additive manufacturing with a methacrylic photopolymer material. Injection moulding was performed using ABS Terluran GP-35 polymer.
3:List of Experimental Equipment and Materials:
Equipment includes a high-precision industrial 3D-printing system, Arburg Allrounder 370A 600-70 Alldrive injection moulding machine, Olympus Lext OLS 4100 laser scanning digital microscope, and SPIP? software for data analysis. Materials include photopolymer for inserts and ABS for moulding.
4:Experimental Procedures and Operational Workflow:
Inserts were designed and printed, then integrated into the mould. IM parameters (melt temperature, injection speed, mould temperature, cooling time) were varied according to DOE. Short shots tests and packing pressure optimization were conducted. IM runs continued until insert failure, with parts analyzed for crack propagation and feature replication using optical metrology.
5:Data Analysis Methods:
Data from optical measurements were processed using SPIP? software. DOE analysis included main effects and interaction plots to determine significant factors. Numerical simulations in COMSOL provided temperature distributions, solidification patterns, and stress analyses.
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