Optimization of the injection molding process for the PC/ABS parts by integrating Taguchi approach and CAE simulation

2019 ◽  
Vol 104 (9-12) ◽  
pp. 4353-4363 ◽  
Author(s):  
Fatma Hentati ◽  
Ismail Hadriche ◽  
Neila Masmoudi ◽  
Chedly Bradai
Keyword(s):  
Injection Molding ◽  
Injection Molding Process ◽  
Taguchi Approach ◽  
Molding Process ◽  
Cae Simulation

Design of Optimization Parameters with Hybrid Genetic Algorithm Method in Multi-Cavity Injection Molding Process

2012 ◽  
Vol 463-464 ◽  
pp. 587-591 ◽  
Author(s):  
Wen Jong Chen ◽  
Jia Ru Lin
Keyword(s):  
Genetic Algorithm ◽  
Injection Molding ◽  
Hybrid Genetic Algorithm ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Molding Process ◽  
Optimization Parameters ◽  
Genetic Algorithm Method ◽  
Artificial Neural Network Ann ◽  
Cae Simulation

This paper combines an artificial neural network (ANN) with a traditional genetic algorithm (GA) method, called hybrid genetic algorithm (HGA), to analyze the warpage of multi-cavity plastic injection molding parts. Simulation results indicate that the minimum and the maximum warpage of the hybrid genetic algorithm (HGA) method were lower than that of the traditional GA method and CAE simulation. These results reveal that, when HGA is applied to multi-cavity plastic warpage analysis, the optimal process conditions are significantly better than those using the traditional GA method or CAE simulation.

Determination of Optimal Microminiature Powder Injection Molding Parameters by Taguchi Approach

2011 ◽  
Vol 189-193 ◽  
pp. 2997-3000
Author(s):  
Haw Pei Li ◽  
Norhamidi Muhamad
Keyword(s):  
Stainless Steel ◽  
Injection Molding ◽  
High Performance ◽  
Injection Pressure ◽  
Steel Powder ◽  
Powder Injection Molding ◽  
Powder Injection ◽  
Injection Molding Process ◽  
Taguchi Approach ◽  
Molding Process

The global manufacturing trend is now focusing towards miniaturization. Microminiature Powder Injection Molding (μPIM) is a viable technology to fabricate complex and high performance miniaturized components. The μPIM technique was used to produce the near-net shape micro components in this study. Fine stainless steel powder with particle size of 5μm was mixed with a ternary water-based binder system. Micro dumbbells with the largest dimension of 9mm were replicated. In order to obtain successful and well molded micro dumbbells, the Design of Experiments (DOE) technique was applied to investigate the optimal parameters in injection molding process. Injection parameters such as injection pressure (A), injection temperature (B), powder loading (C), mold temperature (D), injection time (E) and holding time (F) were optimized by using stainless steel feedstocks. Taguchi approach is chosen and the results were evaluated with signal-to-noise (SN) ratio and analysis of variance (ANOVA). The results show that the feedstocks could be replicated by using μPIM method with the application of Taguchi approach.

Filling Behavior of Polymer Material into Sub-^|^mu;m Structure in Injection Molding Process

2013 ◽  
Vol 133 (4) ◽  
pp. 105-111
Author(s):  
Chisato Yoshimura ◽  
Hiroyuki Hosokawa ◽  
Koji Shimojima ◽  
Fumihiro Itoigawa
Keyword(s):  
Injection Molding ◽  
Polymer Material ◽  
Injection Molding Process ◽  
Molding Process

scholarly journals Study on External Gas-Assisted Mold Temperature Control with the Assistance of a Flow Focusing Device in the Injection Molding Process

Materials ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 965 ◽  
Author(s):  
Nguyen Truong Giang ◽  
Pham Son Minh ◽  
Tran Anh Son ◽  
Tran Minh The Uyen ◽  
Thanh-Hai Nguyen ◽  
...  
Keyword(s):  
Injection Molding ◽  
Temperature Control ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Melt Flow ◽  
Flow Focusing ◽  
Molding Process ◽  
Heating Efficiency ◽  
Flow Length ◽  
Insert Plate

In the injection molding field, the flow of plastic material is one of the most important issues, especially regarding the ability of melted plastic to fill the thin walls of products. To improve the melt flow length, a high mold temperature was applied with pre-heating of the cavity surface. In this paper, we present our research on the injection molding process with pre-heating by external gas-assisted mold temperature control. After this, we observed an improvement in the melt flow length into thin-walled products due to the high mold temperature during the filling step. In addition, to develop the heating efficiency, a flow focusing device (FFD) was applied and verified. The simulations and experiments were carried out within an air temperature of 400 °C and heating time of 20 s to investigate a flow focusing device to assist with external gas-assisted mold temperature control (Ex-GMTC), with the application of various FFD types for the temperature distribution of the insert plate. The heating process was applied for a simple insert model with dimensions of 50 mm × 50 mm × 2 mm, in order to verify the influence of the FFD geometry on the heating result. After that, Ex-GMTC with the assistance of FFD was carried out for a mold-reading process, and the FFD influence was estimated by the mold heating result and the improvement of the melt flow length using acrylonitrile butadiene styrene (ABS). The results show that the air sprue gap (h) significantly affects the temperature of the insert and an air sprue gap of 3 mm gives the best heating rate, with the highest temperature being 321.2 °C. Likewise, the actual results show that the height of the flow focusing device (V) also influences the temperature of the insert plate and that a 5 mm high FFD gives the best results with a maximum temperature of 332.3 °C. Moreover, the heating efficiency when using FFD is always higher than without FFD. After examining the effect of FFD, its application was considered, in order to improve the melt flow length in injection molding, which increased from 38.6 to 170 mm, while the balance of the melt filling was also clearly improved.

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