Processability Testing of Injection Molding Rubber Compounds

1984 ◽  
Vol 57 (4) ◽  
pp. 826-842 ◽  
Author(s):  
John A. Sezna ◽  
P. J. DiMauro

Abstract A simple model of the injection molding process has been constructed using data from a capillary rheometer (MPT) and the Oscillating Disk Rheometer (ODR). For an NR and an SBR compound, the model had an excellent correlation with injection molding trials. The model successfully predicted the effects of adjusting injection pressure, mold temperature, and barrel temperature on injection times and scorch conditions. Such a model enables an injection molder to predict the effect of adjusting molding conditions, optimize his process for a given mold and compound, and control processability of his compounds batch-to-batch.

Author(s):  
Catalin Fetecau ◽  
Ion Postolache ◽  
Felicia Stan

The research presented in this paper involves numerical and experimental efforts to investigate the relative thin-wall injection molding process in order to obtain high dimensional quality complex parts. To better understand the effects of various processing parameters (the filling time, injection pressure, the melting temperature, the mold temperature) on the injection molding of a thin-wall complex part, the molding experiments are regenerated into the computer model using the Moldflow Plastics Insight (MPI) 6.1 software. The computer visualization of the filling phase allows accurate prediction of the location of the flow front, welding lines and air traps. Furthermore, in order to optimize the injection molding process, the effects of the geometry of the runner system on the filling and packing phases are also investigated. It is shown that computational modeling could be used to help the process and mold designer to produce accurate parts.


2011 ◽  
Vol 189-193 ◽  
pp. 537-540
Author(s):  
Jia Min Zhang ◽  
Ming Yi Zhu ◽  
Zhao Xun Lian ◽  
Rong Zhu

The use of L27 (35) orthogonal to the battery shell injection molding process is optimized. The main factors of technical parameters were determined mould temperature, melt temperature, the speed of injection, injection pressure, cooling time.On the basis of actual production, to determine the factors values of different process parameters.Combination of scrapped products in key (reduction and a high degree of tolerance deflated) tests were selected in the process parameters within the scope of the assessment. Various factors impact on the product of the total height followed by cooling time, mold temperature, melt temperature, injection pressure, injection speed from strong to weak .The best products technological parameters were determined.Good results were obtained for production.


2013 ◽  
Vol 734-737 ◽  
pp. 2725-2729
Author(s):  
Yin Wu Tan ◽  
You Min Wang ◽  
Ge Zhou ◽  
Xiao Yang Du

By the use of UG software,the solid model of the interior decoration board inside the automobile door was created and the molding behavior of the plastic product was simulated and analysis in the virtue of Moldflow.Based on the analysis of the effect of the mould parameter on the molding behavior ,the best gate location was achieved.We designed the L9(33) orthogonal experiment table of the parts injection molding,selected the mold temperature, melt temperature, injection pressure as the factores .Sink mark index, volume shrinkage, maximumwarping deformation and cavity residual stress are determined as the parts quality evaluation. We completed the orthogonal experiment and the range analyses of the results. We analyzed the influence of process parameters on evaluation of every optimal direction,developed evaluation for comprehensive quality of parts. Finally, we get the table showing the tendency on the assessment of the quality index influenced by various factors, which provides a foundation for the approaching research on the parameters of the injection molding process.


2009 ◽  
Vol 82 (1) ◽  
pp. 62-93 ◽  
Author(s):  
A. Arrillaga ◽  
A. M. Zaldua ◽  
R. M. Atxurra ◽  
A. S. Farid ◽  
A. S. Farid

Abstract In order to fill the mold in a rubber injection molding process, it is necessary to inject the material into the closed mold. Rubber is usually injected under ram speed control, but it can be also injected under pressure control. In the present study, we have recorded the signals of pressure at three points during the filling of a spiral shape part. The behaviors of two rubber compounds have been studied using a variety of combinations of process conditions (including mold temperature, mass temperature, ram speed and injection molding with and without pressure holding stage). In all conditions, the transducer located in proximity to the gate exhibits pressure decay at the last stage of mold filling. Initial CAE simulations have been carried out using Moldflow software to check the capability of this sort of software to calculate pressure decay during the filling stage.


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 ◽  
...  

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.


2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Youmin Wang ◽  
Zhichao Yan ◽  
Xuejun Shan

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.


2007 ◽  
Vol 4 (2) ◽  
pp. 1
Author(s):  
Muhammad Hussain Ismail ◽  
Norhamidi Muhamad ◽  
Aidah Jumahat ◽  
Istikamah Subuki ◽  
Mohd Afian Omar

Metal Injection Molding (MIM) is a wellestablished technology for manufacturing a variety of complex and small precision parts. In this paper, fundamental rheological characteristics of MIM feedstock using palm stearin are theoretically analyzed and presented. The feedstock consisted of gas atomized 316L stainless steel powder at three different particle size distributions and the binder system of palm stearin (PS) and polyethylene (PE). The powder loading used was 60vol % for all samples (monosize 16 µm, monosize 45 µm, and bimodal 16 µm + 45 µm) and the binder system of 40vol %(PS/PE = 40/60). The viscosity of MIM feedstock at different temperatures and shear rates was measured and evaluated. Results showed that, the feedstock containing palm stearin exhibited suitable rheological properties by increasing the fluidity of feedstock in MIM process. The rheological results also showed a pseudoplastic flow characteristics, which poses higher value of shear sensitivity (n) and lower value of flow activation energy (E), that are both favourable for injection molding process. The green parts were successfully injected and exhibited adequate strength for handling by optimizing the injection pressure and temperature.


2020 ◽  
Vol 40 (9) ◽  
pp. 783-795
Author(s):  
Sara Liparoti ◽  
Vito Speranza ◽  
Annarita De Meo ◽  
Felice De Santis ◽  
Roberto Pantani

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.


2013 ◽  
Vol 345 ◽  
pp. 586-590 ◽  
Author(s):  
Xiao Hong Tan ◽  
Lei Gang Wang ◽  
Wen Shen Wang

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


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