scholarly journals Experimental and Numerical Study Determining the Warpage Phenomenon of Thin-Wall Injection Molding

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yueh-Tzu Huang ◽  
Chiung-Fang Huang ◽  
Bou-Yue Peng ◽  
Chun-Wei Chang ◽  
Hsing-Chung Cheng ◽  
...  
Keyword(s):  
Injection Molding ◽  
Numerical Study ◽  
Numerical Control ◽  
Thin Wall ◽  
Processing Parameter ◽  
Melt Temperature ◽  
Injection Speed ◽  
Thin Walled ◽  
Wall Injection ◽  
Packing Time

This study emphasizes the warpage phenomenon of thin-walled parts using acrylonitrile-butadiene styrene (ABS) plus polycarbonate (PC) plastics for optimal processing by thin-wall injection molding. The authors first employed the Moldflow software to analyze the runner’s balance on multicavities for thin-walled parts and to simulate the warpage of thin-walled parts with thin-wall injection molding. Then, this study used those data to fabricate a real mold by computer numerical control machining. For this study, the authors fabricated thin-walled parts and measured their warpage using various process parameters (injection speed, injection pressure, mold temperature, packing time, and melt temperature) with thin-walled injection molding. Finally, the authors found that the most important processing parameter was the packing time for warpage phenomenon of thin-walled parts by thin-wall injection molding.

The simulation of the warpage rule of the thin-walled part of polypropylene composite based on the coupling effect of mold deformation and injection molding process

2018 ◽  
Vol 25 (3) ◽  
pp. 593-601 ◽  
Author(s):  
Jixiang Zhang ◽  
Xiaoyi Yin ◽  
Fengzhi Liu ◽  
Pan Yang
Keyword(s):  
Injection Molding ◽  
Coupling Effect ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Plastic Part ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure ◽  
Thin Walled ◽  
Packing Time

Abstract Aiming at the problem that a thin-walled plastic part easily produces warpage, an orthogonal experimental method was used for multiparameter coupling analysis, with mold structure parameters and injection molding process parameters considered synthetically. The plastic part deformation under different experiment schemes was comparatively studied, and the key factors affecting the plastic part warpage were analyzed. Then the injection molding process was optimized. The results showed that the important order of the influence factors for the plastic part warpage was packing pressure, packing time, cooling plan, mold temperature, and melt temperature. Among them, packing pressure was the most significant factor. The optimal injection molding process schemes reducing the plastic part warpage were melt temperature (260°C), mold temperature (60°C), packing pressure (150 MPa), packing time (2 s), and cooling plan 3. In this situation, the forming plate flatness was better.

Investigation of mold plate separation in thin-wall injection molding

2003 ◽  
Vol 22 (4) ◽  
pp. 306-319 ◽  
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

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

2019 ◽  
Vol 18 (01) ◽  
pp. 85-102 ◽  
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.

Effects of process parameters on the formability of sheet metal during plastic injection forming

2020 ◽  
Vol 62 (5) ◽  
pp. 535-543
Author(s):  
Mirigul Altan ◽  
Bora Sener ◽  
Mirigul Altan
Keyword(s):  
Injection Molding ◽  
Sheet Metal ◽  
Injection Pressure ◽  
Industrial Applications ◽  
Effective Parameter ◽  
Melt Temperature ◽  
Injection Speed ◽  
Aluminum Sheets ◽  
Plastic Injection ◽  
Thinning Rate

Abstract Plastic injection forming (PIF) is an alternative sheet metal forming method for complex geometrical parts with dimensions in low tolerance. This method is a combination of injection molding and hydroforming in which a molten polymer material has been injected over a sheet metal via a plastic injection molding machine. In this study, aluminum sheets 1.5 mm thick were shaped by PIF at various injection pressures, melt temperatures and injection speed. The effects of these parameters on the formability of the sheet metal were investigated using the experimental design technique. The thinning rate, flange radius and the hardness values of the shaped sheets were considered in the experimental study. Injection pressure was found to be the most effective parameter and melt temperature was the second degree effective parameter for the thinning rate. The usability of the PIF process in industrial applications as an alternative method was emphasized by comparing PIF with conventional hydroforming by means of the finite element method (Ls-Dyna). A 2.07 % deviation was observed between the FE results for hydroforming and the experimental results for PIF.

Anisotropic multilayer conductive networks in carbon nanotubes filled polyethylene/polypropylene blends obtained through high speed thin wall injection molding

Polymer ◽  
2013 ◽  
Vol 54 (23) ◽  
pp. 6425-6436 ◽  
Author(s):  
Feilong Yu ◽  
Hua Deng ◽  
Qin Zhang ◽  
Ke Wang ◽  
Chaoliang Zhang ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Injection Molding ◽  
High Speed ◽  
Thin Wall ◽  
Wall Injection ◽  
Polypropylene Blends

Analysis of Residual Stress in Thin Wall Injection Molding

2006 ◽  
Vol 306-308 ◽  
pp. 1331-1336
Author(s):  
H.K. Lee ◽  
J.C. Huang ◽  
G.E. Yang ◽  
Hong Gun Kim
Keyword(s):  
Residual Stress ◽  
Stress Distribution ◽  
Injection Molding ◽  
Molecular Orientation ◽  
Polymeric Materials ◽  
Residual Stress Distribution ◽  
Thin Wall ◽  
Flow Paths ◽  
Wall Injection ◽  
Relationship Of

A relationship of residual stress distribution and surface molding states on polymeric materials is presented in thin-walled injection molding. The residual stress is computed by computational numerical analysis, observed with stress viewer and birefringence. The residual stress on polymeric parts can allude the surface quality as well as flow paths. The residual stress distribution on polymeric parts is related with thickness, gate layout, and polymer types. Molecular orientation on polymeric parts is also important in thin wall injection molding. The residual stress and molecular orientation are related to the surface molding states intimately. Analysis of the residual stress is validated through photo-elastic method and surface molding states..

scholarly journals The Feasibility of an Internal Gas-Assisted Heating Method for Improving the Melt Filling Ability of Polyamide 6 Thermoplastic Composites in a Thin Wall Injection Molding Process

Polymers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1004 ◽  
Author(s):  
Thanh Trung Do ◽  
Tran Minh The Uyen ◽  
Pham Son Minh
Keyword(s):  
Injection Molding ◽  
Heating Rate ◽  
Temperature Control ◽  
Cavity Surface ◽  
Heating Process ◽  
Injection Molding Process ◽  
Thin Wall ◽  
Molding Process ◽  
Filling Ability ◽  
Wall Injection

In thin wall injection molding, the filling of plastic material into the cavity will be restricted by the frozen layer due to the quick cooling of the hot melt when it contacts with the lower temperature surface of the cavity. This problem is heightened in composite material, which has a higher viscosity than pure plastic. In this paper, to reduce the frozen layer as well as improve the filling ability of polyamide 6 reinforced with 30 wt.% glass fiber (PA6/GF30%) in the thin wall injection molding process, a preheating step with the internal gas heating method was applied to heat the cavity surface to a high temperature, and then, the filling step was commenced. In this study, the filling ability of PA6/GF30% was studied with a melt flow thickness varying from 0.1 to 0.5 mm. To improve the filling ability, the mold temperature control technique was applied. In this study, an internal gas-assisted mold temperature control (In-GMTC) using different levels of mold insert thickness and gas temperatures to achieve rapid mold surface temperature control was established. The heating process was observed using an infrared camera and estimated by the temperature distribution and the heating rate. Then, the In-GMTC was employed to produce a thin product by an injection molding process with the In-GMTC system. The simulation results show that with agas temperature of 300 °C, the cavity surface could be heated under a heating rate that varied from 23.5 to 24.5 °C/s in the first 2 s. Then, the heating rate decreased. After the heating process was completed, the cavity temperature was varied from 83.8 to about 164.5 °C. In-GMTC was also used for the injection molding process with a part thickness that varied from 0.1 to 0.5 mm. The results show that with In-GMTC, the filling ability of composite material clearly increased from 2.8 to 18.6 mm with a flow thickness of 0.1 mm.

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