Mold-Flow analysis in injection molding process of fan back cover

Author(s):  
Hong-mei Kang ◽  
Yuan-sheng Wang ◽  
Lin-hong Xu
2013 ◽  
Vol 690-693 ◽  
pp. 2344-2351 ◽  
Author(s):  
Wen Chin Chen ◽  
Li Yi Wang ◽  
Cheng Chi Huang ◽  
Tung Tsan Lai

This study proposes a parameter optimization system for a multi-LED lighting lens, which uses design of experiment (DOE) for screening the process parameters, computer-aided engineering (CAE) for mold flow analysis, analysis of variance (ANOVA) for determining the significant parameters, and response surface methodology (RSM) for finding the initial parameter settings in terms of multi-objective quality characteristics. In addition, two regression models, obtained from RSM, are employed as the quality predictors which are combined with the particle swarm optimization (PSO) to generate the optimal molding parameter settings. The numerical results show that the proposed approach, RSM with PSO, is beneficial to obtain the better process parameter settings in the injection molding process.


2012 ◽  
Vol 482-484 ◽  
pp. 470-473 ◽  
Author(s):  
Shi Qiang Zhang ◽  
Hai Sheng Liu ◽  
Hui Gang Wang ◽  
Xiao Wen Liu

In order to acquire the best filling time, Mold trial is made by setting different injection time, or Moldflow software is used to analysis data recorded by computer. Whether doing successive trials or being simulated point by point, is very tedious. Put forward a method of using the Lagrange to simulate a curve based on the mold flow analysis, the minimum of the curve is the best filling time. This method can gain the best filling time as quickly as possible, and improve the efficiency of the mold flow analysis.


2020 ◽  
Vol 311 ◽  
pp. 64-73
Author(s):  
Dyi Cheng Chen ◽  
Kuo Cheng Wen ◽  
Rih Sheng Yang ◽  
Yu Yu Lai

With the advancement of technology, plastic products are inseparable in our environment, and the impact of the plastics industry on us is gradually increasing. Although Taiwan's plastics industry has been progressively added to mold flow analysis and automation, there are still some areas in the manufacturing process that can be optimized. In the process of slit-shaped materials, bending and deformation have a very large impact on the finished product, which is a major issue at the technical level. In this study, a toothbrush was taken as an example to find the best combination of injection molding parameters. The research process was studied from CAD mold design, CAE mold flow analysis, injection molding parameter analysis, mold opening, product injection and measurement, and the results were verified. Among them, the injection pressure, dwell time and holding pressure are used as the Taguchi factor, and the CAE mold flow analysis is performed by the direct cross table L16 (45) combination to find a small amount of warpage, and the Taguchi method and the reaction surface method are used to find out the best combination of parameters. After the final product was shot and the dimensions and simulation were compared with each other, the data showed that the amount of warpage of the finished product was 0.0892 mm, and the error with the analog value was 0.0212 mm, which confirmed that the injection molding parameters were reliable.


This paper is based on the plastic flow simulation of a thin Fresnel lens to estimate the injection molding process. Nowadays Fresnel lenses are made of transparent plastics materials instead of silica-based glass to reduce handling and processing cost. For mass manufacturing of plastic parts, the injection molding process is best suited. Thus in this study plastic flow analysis of a thin Fresnel lens is carried for the evaluation of injection molding process. Plastic flow analysis helps in estimating how molten plastic will flow during the process Plastic flow analysis is also very helpful in evaluating the manufacturing defects such as air traps and weld lines without real-time experimentation. The simulation results evaluate the values of the parameters such as fill time, filing pressure, pack pressure, etc. Also, the manufacturing defects observed by the simulation results are reasonable and met the design requirement.


Author(s):  
D M Nuruzzaman ◽  
N Kusaseh ◽  
S Basri ◽  
A N Oumer ◽  
Z Hamedon

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