scholarly journals Determined Car Door Latch Injection Molding Process Conditions through the Finite Elements Analysis

2016 ◽  
Vol 17 (10) ◽  
pp. 499-508 ◽  
Author(s):  
Jung-Hyun Lee ◽  
Seon-Bong Lee
Keyword(s):  
Finite Elements ◽  
Injection Molding ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Molding Process ◽  
Finite Elements Analysis

scholarly journals Experimental Validation of Injection Molding Simulations of 3D Microparts and Microstructured Components Using Virtual Design of Experiments and Multi-Scale Modeling

Micromachines ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 614 ◽  
Author(s):  
Dario Loaldi ◽  
Francesco Regi ◽  
Federico Baruffi ◽  
Matteo Calaon ◽  
Danilo Quagliotti ◽  
...  
Keyword(s):  
Injection Molding ◽  
Process Simulation ◽  
Current Work ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Virtual Design ◽  
Molding Process ◽  
Micro Injection Molding ◽  
Multi Scale ◽  
Filling Time

The increasing demand for micro-injection molding process technology and the corresponding micro-molded products have materialized in the need for models and simulation capabilities for the establishment of a digital twin of the manufacturing process. The opportunities enabled by the correct process simulation include the possibility of forecasting the part quality and finding optimal process conditions for a given product. The present work displays further use of micro-injection molding process simulation for the prediction of feature dimensions and its optimization and microfeature replication behavior due to geometrical boundary effects. The current work focused on the micro-injection molding of three-dimensional microparts and of single components featuring microstructures. First, two virtual a studies were performed to predict the outer diameter of a micro-ring within an accuracy of 10 µm and the flash formation on a micro-component with mass a 0.1 mg. In the second part of the study, the influence of microstructure orientation on the filling time of a microcavity design section was investigated for a component featuring micro grooves with a 15 µm nominal height. Multiscale meshing was employed to model the replication of microfeatures in a range of 17–346 µm in a Fresnel lens product, allowing the prediction of the replication behavior of a microfeature at 91% accuracy. The simulations were performed using 3D modeling and generalized Navier–Stokes equations using a single multi-scale simulation approach. The current work shows the current potential and limitations in the use of micro-injection molding process simulations for the optimization of micro 3D-part and microstructured components.

Experimental determination of friction coefficients between thermoplastics and rapid tooled injection mold materials

2005 ◽  
Vol 11 (3) ◽  
pp. 167-173 ◽  
Author(s):  
Mary E. Kinsella ◽  
Blaine Lilly ◽  
Benjamin E. Gardner ◽  
Nick J. Jacobs
Keyword(s):  
Injection Molding ◽  
Accurate Determination ◽  
Rapid Tooling ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Molding Process ◽  
Friction Coefficients ◽  
Content Type ◽  
Temperature Conditions

PurposeTo determine static friction coefficients between rapid tooled materials and thermoplastic materials to better understand ejection force requirements for the injection molding process using rapid‐tooled mold inserts.Design/methodology/approachStatic coefficients of friction were determined for semi‐crystalline high‐density polyethylene (HDPE) and amorphous high‐impact polystyrene (HIPS) against two rapid tooling materials, sintered steel with bronze (LaserForm ST‐100) and stereolithography resin (SL5170), and against P‐20 mold steel. Friction tests, using the ASTM D 1894 standard, were run for all material pairs at room temperature, at typical part ejection temperatures, and at ejection temperatures preceded by processing temperatures. The tests at high temperature were designed to simulate injection molding process conditions.FindingsThe friction coefficients for HDPE were similar on P‐20 Steel, LaserForm ST‐100, and SL5170 Resin at all temperature conditions. The HIPS coefficients, however, varied significantly among tooling materials in heated tests. Both polymers showed highest coefficients on SL5170 Resin at all temperature conditions. Friction coefficients were especially high for HIPS on the SL5170 Resin tooling material.Research limitations/implicationsApplications of these findings must consider that elevated temperature tests more closely simulated the injection‐molding environment, but did not exactly duplicate it.Practical implicationsThe data obtained from these tests allow for more accurate determination of friction conditions and ejection forces, which can improve future design of injection molds using rapid tooling technologies.Originality/valueThis work provides previously unavailable friction data for two common thermoplastics against two rapid tooling materials and one steel tooling material, and under conditions that more closely simulate the injection‐molding environment.

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.

scholarly journals Effects of Injection Molding Process Conditions on Physical Properties of EPDM Using Design of Experiment Method

2018 ◽  
Vol 167 ◽  
pp. 02016 ◽  
Author(s):  
Young Shin Kim ◽  
Euy Sik Jeon ◽  
Eui Seob Hwang
Keyword(s):  
Injection Molding ◽  
Physical Properties ◽  
Raw Material ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Process Variables ◽  
Molding Process ◽  
Test Pieces ◽  
Experiment Method ◽  
Major Factors

The process variables such as time and temperature during the EPDM-injection molding not only change the physical properties of the raw material but also affect the insertion and separations forces when a grommet product is molded and mounted on a car body. Using the design of experiments method, the major factors in the injection molding process were considered to analyze their effects on the physical properties of the obtained EPDM materials. Test pieces were prepared under different process conditions, tensile strength and elongation were measured, and their correlation was analyzed.

Influence of Injection Molding Parameters on the Consistency of Molding Process

2013 ◽  
Vol 446-447 ◽  
pp. 398-402
Author(s):  
S. Azmoudeh ◽  
H. Zamani ◽  
K. Shelesh-Nezhad
Keyword(s):  
Injection Molding ◽  
Signal To Noise Ratio ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Cavity Pressure ◽  
Molding Process ◽  
Injection Speed ◽  
Taguchi Design Of Experiments ◽  
Pressure Profiles ◽  
Molded Parts

The existence of variations in the injection molding process conditions leads to the inconsistency of molded parts quality during the molding cycles. In this research, the variations of cavity pressure-time profiles integrals over the molding cycles were accounted as the molded parts quality variations. Thereafter, the correlations between injection molding process settings and the degree of consistency of molding process were investigated by applying cavity pressure measurement, Taguchi design of experiments approach and signal to noise ratio. The results derived from experiments indicated that an increase approximately as high as five times in the capability of injection molding may be achieved. Under the best setting condition, the cavity pressure profiles were relatively smooth and similar. Low screw rotational speed, high injection speed and short packing time led to the inconsistency elevation of injection molding.

Die Pressure Losses During Injection Molding of Rubber Mixes

2009 ◽  
Vol 82 (1) ◽  
pp. 62-93 ◽  
Author(s):  
A. Arrillaga ◽  
A. M. Zaldua ◽  
R. M. Atxurra ◽  
A. S. Farid ◽  
A. S. Farid
Keyword(s):  
Injection Molding ◽  
Pressure Control ◽  
Mold Temperature ◽  
Injection Molding Process ◽  
Process Conditions ◽  
Molding Process ◽  
Pressure Losses ◽  
Pressure Decay ◽  
Rubber Compounds ◽  
Ram Speed

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.

Sign in / Sign up

Export Citation Format

Share Document