Injection Molding for a Ultra Thin-Wall Part using Induction Heating

In injection molding, the temperature control of the dynamic mold is an excellent method for improving the melt flow length, especially of thin-wall products. In this study, the heating efficiency of a novel heating strategy based on induction heating was estimated. With the use of this heating strategy, a molding cycle time similar to the traditional injection molding process could be maintained. In addition, this strategy makes it easier to carry out the heating step due to the separation of the heating position and the mold structure as well as allowing the ease of magnetic control. The results show that, with an initial mold temperature of 30 °C and a gap (G) between the heating surface and the inductor coil of 5 mm, the magnetic heating process can heat the plate to 290 °C within 5 s. However, with a gap of 15 mm, it took up to 8 s to reach 270 °C. According to the measurement results, when the mold heating time during the molding process increased from 0 to 5 s, the flow length increased significantly from 71.5 to 168.1 mm, and the filling percentage of the thin-wall product also increased from 10.2% to 100%. In general, the application of external induction heating (Ex-IH) during the molding cycle resulted in improved melt flow length with minimal increase in the total cycle time, which remained similar to that of the traditional case.

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Optimization of High Performance Engineering Plastics in Thin Wall Part Injection Molding

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.213.58 ◽

2011 ◽

Vol 213 ◽

pp. 58-62 ◽

Cited By ~ 1

Author(s):

Te Li Su ◽

Fu Chen Kung ◽

Yu Lin Kuo

Keyword(s):

Injection Molding ◽

High Performance ◽

Injection Molding Process ◽

Thin Wall ◽

Molding Process ◽

Performance Engineering ◽

Engineering Plastics ◽

Trial And Error Method ◽

Grey Relational ◽

Thin Wall Part

The purpose of this study is to improve the qualities of thin wall part injection molding using polypropylene. The shape of injection molding products is getting more and more complex now, and the requirement for accuracy is also getting higher. The traditional trial and error method and rules of experience cannot be used well at all. This study applied Taguchi method and grey relational analysis to optimize the injection molding process for obtaining multiple quality characteristics of thin wall parts. The experimental results verify the reliability of optimum conditions via confirmation experiment.

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Temperature Dependence and Magnetic Properties of Injection Molding Tool Materials Used in Induction Heating

IEEE Transactions on Magnetics ◽

10.1109/tmag.2015.2428215 ◽

2015 ◽

Vol 51 (9) ◽

pp. 1-7 ◽

Cited By ~ 6

Author(s):

Patrick Guerrier ◽

Kaspar K. Nielsen ◽

Jesper H. Hattel

Keyword(s):

Magnetic Properties ◽

Injection Molding ◽

Temperature Dependence ◽

Induction Heating ◽

Tool Materials ◽

Materials Used ◽

Molding Tool

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Investigation of mold plate separation in thin-wall injection molding

Advances in Polymer Technology ◽

10.1002/adv.10058 ◽

2003 ◽

Vol 22 (4) ◽

pp. 306-319 ◽

Cited By ~ 9

Author(s):

Shia-Chung Chen ◽

Wei-Liang Liaw ◽

Pao-Lin Su ◽

Ming-Hsiu Chung

Keyword(s):

Injection Molding ◽

Thin Wall ◽

Mold Plate ◽

Plate Separation ◽

Wall Injection

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Warpage and Shrinkage Analysis and Optimization of Rapid Tooling Molded thin Wall Component Using Modified Particle Swarm Algorithm

Journal of Advanced Manufacturing Systems ◽

10.1142/s0219686719500045 ◽

2019 ◽

Vol 18 (01) ◽

pp. 85-102 ◽

Cited By ~ 2

Author(s):

Sagar Kumar ◽

Amit Kumar Singh

Keyword(s):

Injection Molding ◽

Process Parameters ◽

Simulation Analysis ◽

Statistical Significance ◽

Particle Swarm ◽

Processing Parameters ◽

Particle Swarm Algorithm ◽

Thin Wall ◽

Polybutylene Terephthalate ◽

Melt Temperature

This paper presents a systematic methodology to determine optimal injection molding conditions for minimum warpage and shrinkage in a thin wall relay part using modified particle swarm optimization algorithm (MPSO). Polybutylene terephthalate (PBT) and polyethylene terephthalate (PET) were injected in a thin wall relay component for different processing parameters: melt temperature, packing pressure and packing time. Further, Taguchi’s L9 (3[Formula: see text] orthogonal array is used for conducting simulation analysis to consider the interaction effects of the above parameters. A predictive mathematical model for shrinkage and warpage is developed in terms of the above process parameters using regression analysis. ANOVA analysis is performed to establish statistical significance within the injection molding parameters. The analytical model is further optimized using a newly developed MPSO algorithm and the process parameters values are predicted for minimizing shrinkage and warpage. The predicted values of shrinkage and warpage using MPSO algorithm are improved by approximately 30% as compared to the initial simulation values and comparable to previous literature results.

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