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Updated: May 30, 2025

A Soft Tooling Process Chain for Injection Molding of a 3D Component with Micro Pillars
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Nozzle Pressure- and Screw Position-Based CAE Scientific Process Parameter Setup for Injection Molding Process.

Ren-Ho Tseng1, Chien-Hung Wen1, Chen-Hsiang Chang1

  • 1Department of Mechanical Engineering, National Cheng Kung University, Tainan 701401, Taiwan.

Polymers
|January 25, 2025
PubMed
Summary

This study calibrated injection molding simulations using a time constant, significantly reducing errors in injection speed and V/P switchover position. This improved simulation accuracy aligns experimental and simulated process parameters.

Keywords:
injection moldinginjection molding CAE simulationnozzle pressurescientific process parameter setupscrew position

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Area of Science:

  • Materials Science
  • Manufacturing Engineering
  • Computational Modeling

Background:

  • Accurate simulation of injection molding processes is crucial for optimizing manufacturing.
  • Previous studies often lacked precise calibration, leading to discrepancies between simulated and experimental results.
  • Machine response variability introduces errors in real-world process parameter setups.

Purpose of the Study:

  • To develop a scientific process parameter setup for injection molding experiments and simulations.
  • To implement and validate a calibration method for improving simulation accuracy.
  • To reduce the error between simulated and experimental process parameters.

Main Methods:

  • Established a scientific process parameter setup focusing on nozzle pressure and screw position.
  • Defined a parameter search sequence: injection speed, V/P switchover position, packing pressure, and packing time.
  • Implemented time constant calibration to align simulation outputs with experimental data.

Main Results:

  • Experiments and simulations showed similar trends in process parameter setup.
  • Uncalibrated simulations exhibited parameter errors due to machine response.
  • Time constant calibration significantly reduced injection speed error from 20% to 6%.
  • V/P switchover point error decreased from 11% to 5% after calibration.

Conclusions:

  • Time constant calibration is effective in enhancing the accuracy of injection molding simulations.
  • Calibrated simulations provide results closer to experimental data, improving process optimization.
  • This approach bridges the gap between simulation and experimental validation in manufacturing.