scholarly journals Fill Time Optimization Analysis In Flow Simulation Of Injection Molding Using Response Surface Method

2021 ◽  
Vol 4 (1) ◽  
pp. 28-39
Author(s):  
Mohd Amran Md Ali ◽  
Wan Nur Azrina ◽  
Noorfa Idayu ◽  
Zulkeflee Abdullah ◽  
Mohd Sanusi Abdul Aziz ◽  
...  
Keyword(s):  
Injection Molding ◽  
Response Surface ◽  
Response Surface Method ◽  
Weld Line ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Injection Time ◽  
Molding Process ◽  
Optimum Parameters ◽  
Surface Method

This study focuses on the analysis of fill time by optimizing the injection molding parameters to reduce the defects that are always found on the plastics part such as poor weld line and part not completely filling which can contribute to mechanical properties of the plastic part. The parameters selected for this study are melting temperature, mold temperature, injection time, and the number of gate positions. Response Surface Method (RSM) was used to determine the most significant and optimum parameters on the fill time. From the result analysis, it is found that the injection time is the most significant parameter that affected the fill time with a 99% contribution. The result shows that there is no interaction between process parameters toward fill time which the injection time is the only major factor that affects the fill time. The improvement increases by 0.07% after the optimization process from 4.278s to 4.281s. The most optimum parameters to longer the injection time are mold temperature at 60°C, injection time at 4s, and the number of the gate with two gates position. Thus, the longer the injection time, it can reduce the defect of molded part in the injection molding process.

The Application of Moldflow in Injection Molding of the Helmet

2015 ◽  
Vol 1096 ◽  
pp. 366-370
Author(s):  
Yong Cheng Huang ◽  
Hong Bin Liu ◽  
Hai Tao Wu
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Hold Time ◽  
Mold Temperature ◽  
Appropriate Technology ◽  
Injection Molding Process ◽  
Injection Time ◽  
Molding Process ◽  
Melt Temperature ◽  
Packing Pressure

Considering the importance of the reasonable injection molding technology.Based on the application of moldflow in injection molding of the helmet .By adjusting the mold temperature, melt temperature, injection time, packing pressure, hold time and so on the injection molding process parameters to develop appropriate technology methods to get the best injection molding parameters.

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.

scholarly journals Optimization of Process Parameters for Vertical-Faced Polypropylene Bottle Injection Molding

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Youmin Wang ◽  
Zhichao Yan ◽  
Xuejun Shan
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Dwell Time ◽  
Optimization Problem ◽  
Injection Pressure ◽  
Mold Temperature ◽  
Orthogonal Test ◽  
Injection Molding Process ◽  
Injection Time ◽  
Melt Temperature

In order to obtain the optimal combination of process parameters for vertical-faced polypropylene bottle injection molding, with UG, the model of the bottle was drawn, and then, one module and sixteen-cavity injection molding system was established and analyzed using Moldflow. For filling and maintaining pressure during the process of infusion bottle injection molding, the orthogonal test table L25 (56) using CAE was designed for injection molding of the bottle, with six parameters such as melt temperature, mold temperature, injection pressure, injection time, dwell pressure, and dwell time as orthogonal test factors. By finding the best combination of process parameters, the orthogonal experiment was completed, the results were analyzed by range analysis, and the order of influence of each process parameter on each direction of optimization was obtained. The prediction dates of the infusion bottle were gained under various parameters, a comprehensive quality evaluation index of the bottle was formulated, and the multiobjective optimization problem of injection molding process was transformed into a single-objective optimization problem by the integrated weighted score method. The bottle parameters were optimized by analyzing the range date of the weighted scoring method, and the best parameter combination such as melt temperature 200°C, mold temperature 80°C, injection pressure 40 MPa, injection time 2.1 S, dwell pressure 40 MPa, and dwell time 40 S was gained.

scholarly journals Prediction of the maximum flow length of a thin injection molded part

2020 ◽  
Vol 40 (9) ◽  
pp. 783-795
Author(s):  
Sara Liparoti ◽  
Vito Speranza ◽  
Annarita De Meo ◽  
Felice De Santis ◽  
Roberto Pantani
Keyword(s):  
Injection Molding ◽  
Maximum Flow ◽  
Mold Temperature ◽  
Complete Characterization ◽  
Rheological Parameters ◽  
Injection Molding Process ◽  
Spiral Flow ◽  
Molding Process ◽  
Molded Part ◽  
Flow Length

AbstractOne of the most significant issues, when thin parts have to be obtained by injection molding (i.e. in micro-injection molding), is the determination of the conditions of pressure, mold temperature, and injection temperature to adopt to completely fill the cavity. Obviously, modern computational methods allow the simulation of the injection molding process for any material and any cavity geometry. However, this simulation requires a complete characterization of the material for what concerns the rheological and thermal parameters, and also a suitable criterion for solidification. These parameters are not always easily reachable. A simple test aimed at obtaining the required parameters is then highly advantageous. The so-called spiral flow test, consisting of measuring the length reached by a polymer in a long cavity under different molding conditions, is a method of this kind. In this work, with reference to an isotactic polypropylene, some spiral flow tests obtained with different mold temperatures and injection pressures are analyzed with a twofold goal: on one side, to obtain from a few simple tests the basic rheological parameters of the material; on the other side, to suggest a method for a quick prediction of the final flow length.

Optimization of Injection Molding Process Parameters with Material Properties Based on GA and BP

2013 ◽  
Vol 345 ◽  
pp. 586-590 ◽  
Author(s):  
Xiao Hong Tan ◽  
Lei Gang Wang ◽  
Wen Shen Wang
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Axial Deformation ◽  
Molding Process ◽  
Melt Temperature ◽  
Bp Network ◽  
Injection Parameters ◽  
Moldflow Simulation

To obtain optimal injection process parameters, GA was used to optimize BP network structure based on Moldflow simulation results. The BP network was set up which considering the relationship between volume shrinkage of plastic parts and injection parameters, such as mold temperature, melt temperature, holding pressure and holding time etc. And the optimal process parameters are obtained, which is agreed with actual results. Using BP network to predict injection parameters impact on parts quality can effectively reduce the difficulty and workload of other modeling methods. This method can be extended to other quality prediction in the process of plastic parts.Keyword: Genetic algorithm (GA);Neural network algorithm (BP);Injection molding process optimization;The axial deformation

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.

Optimization of the Injection Molding Process Parameters Based on Moldflow and Orthogonal Experiment

2013 ◽  
Vol 561 ◽  
pp. 239-243 ◽  
Author(s):  
Yong Nie ◽  
Hui Min Zhang ◽  
Jia Teng Niu
Keyword(s):  
Injection Molding ◽  
Orthogonal Experiment ◽  
Mold Temperature ◽  
Processing Parameters ◽  
Influential Factors ◽  
Injection Molding Process ◽  
Range Analysis ◽  
Molding Process ◽  
Melt Temperature ◽  
Plastic Parts

This article is using Moldflow analysis and orthogonal experimental method during the whole experiment. The injection molding process of motor cover is simulated under various technological conditions.After forming the maximum amount of warpage of plastic parts for evaluation.According to the range analysis of the comprehensive goal, the extent of the overall influence to the processing parameters, such as gate location, melt temperature, mold temperature and holding pressure is clarified.Through analyzing the diagrams of influential factors resulted from the simulation result,the optimized process parameter scheme is obtained and further verified by simulation.

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