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Experimental Characterization and Simulation of Thermoplastic Polymer Flow Hesitation in Thin-Wall Injection Molding
Francesco Regi1, Patrick Guerrier1, Yang Zhang1
1Department of Mechanical Engineering, Technical University of Denmark, Building 427A, Produktionstorvet, DK-2800 Kgs Lyngby, Denmark.
Micromachines
|April 25, 2020
Summary
This study visually analyzed polymer flow in thin-wall injection molding, finding that thickness, velocity, and material type significantly impact flow progression and hesitation. Simulations accurately predicted filling times, validating the process modeling.
Area of Science:
- Materials Science
- Polymer Engineering
- Manufacturing Processes
Background:
- Injection molding is a key manufacturing process for polymers.
- Understanding polymer flow, especially in thin-wall applications, is crucial for product quality.
- Hesitation, a flow interruption phenomenon, can negatively impact molded part integrity.
Purpose of the Study:
- To directly observe and analyze polymer flow progression during thin-wall injection molding.
- To validate simulation models for the injection molding process, focusing on the hesitation effect.
- To investigate the influence of cavity thickness, material type, and processing conditions on flow behavior.
Main Methods:
- Utilized a specialized mold with a glass window for direct visualization.
- Employed a high-speed camera (HSC) recording at 500 frames per second to capture flow dynamics.
- Experimented with acrylonitrile butadiene styrene (ABS) and polypropylene (PP) in staircase-designed cavities of varying thin-wall thicknesses.
- Validated simulations using data from pressure sensors, thermocouples, and machine parameters.
Main Results:
- Flow progression and hesitation were significantly influenced by cavity thickness, polymer velocity, and material type (ABS vs. PP).
- High-speed video recordings provided direct evidence of flow behavior and hesitation phenomena.
- Simulation results showed good agreement with experimental data regarding flow patterns and progression.
- Filling times were predicted with an average relative error of 2.5%, though accuracy decreased in thinner sections.
Conclusions:
- Direct visualization combined with simulation offers a robust method for studying thin-wall injection molding.
- Material type, velocity, and part geometry are critical factors affecting polymer flow and hesitation.
- Simulation models are effective for predicting filling times in injection molding, with potential for optimization in thinner sections.
