scholarly journals Ceramic injection molding material analysis, modeling and injection molding simulation

2014 ◽  
Author(s):  
D. Drummer ◽  
S. Messingschlager
Keyword(s):  
Injection Molding ◽  
Material Analysis ◽  
Molding Material ◽  
Ceramic Injection Molding ◽  
Injection Molding Simulation

Key Technologies Research on Color Contour Map of 3D Injection Molding Simulation Results

2012 ◽  
Vol 217-219 ◽  
pp. 1998-2001
Author(s):  
Tie Geng ◽  
Qing Hai Ren ◽  
Wei Qing Tu ◽  
Dan Dan Liu
Keyword(s):  
Injection Molding ◽  
Color Image ◽  
Three Dimensional ◽  
Physical Field ◽  
Contour Map ◽  
Image Rendering ◽  
Color Range ◽  
Key Technologies ◽  
Injection Molding Simulation ◽  
Simulation Results

According to the color contour map of the 3D injection molding simulation results, the commonly used color contour map drawing algorithm was researched, and a three-dimensional color image rendering algorithm which based on the "physical field values and color range mapping" was given too. And the key technologies of the algorithm which was used to draw 3D color contour map were introduced in detail. In the end, an example was given.

Influence of Carbon Content on Ceramic Injection Molding of Reaction-Bonded Silicon Carbide

2016 ◽  
Vol 13 (5) ◽  
pp. 838-843 ◽  
Author(s):  
Zhao Zhang ◽  
Yujun Zhang ◽  
Hongyu Gong ◽  
Xue Guo ◽  
Yubai Zhang ◽  
...  
Keyword(s):  
Silicon Carbide ◽  
Injection Molding ◽  
Carbon Content ◽  
Ceramic Injection Molding

The Use of Advanced Aluminum Alloys for Enhanced Productivity in Plastic Injection Molding

2000 ◽  
Author(s):  
Jim Nerone ◽  
Karthik Ramani
Keyword(s):  
Aluminum Alloys ◽  
Injection Molding ◽  
Wall Thickness ◽  
Simulation Software ◽  
Cooling Time ◽  
Coolant Temperature ◽  
Steel Mold ◽  
Cooling Channels ◽  
Injection Molding Simulation ◽  
Increased Strength

Abstract New aluminum alloys, QC-7® and QE-7®, have thermal conductivities four times greater than traditional tool steels, and have significantly increased strength and hardness compared to traditional aluminum materials. Molds were constructed of P-20 tool steel and QE-7® aluminum and were used to provide experimental data regarding thermal mold characteristic and confirm injection molding simulation predictions using C-Mold®. The relationships between cooling time reduction (using aluminum alloys) and polymer type, cooling channel depth, part wall thickness, and coolant temperature were explored both experimentally and using simulation software. It was shown that the potential reduction in cooling time varied from 5% to 25%. The most significant percentage improvements were observed in parts with part wall thickness of 0.05″ to 0.10″ and in molds with cooling channels at a depth ratio (D/d) of 2.0. The thermal pulses in the steel mold 0.10″ from the surface were approximately 63% larger than in aluminum mold.

Optimization of fiber prediction model coefficients in injection molding simulation based on micro computed tomography

2018 ◽  
Vol 59 (s2) ◽  
pp. E152-E160 ◽  
Author(s):  
Matthias Morak ◽  
Daniel Tscharnuter ◽  
Thomas Lucyshyn ◽  
Wolfram Hahn ◽  
Michael Göttlinger ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Injection Molding ◽  
Prediction Model ◽  
Micro Computed Tomography ◽  
Simulation Based ◽  
Injection Molding Simulation

Gate Location Optimization in Injection Molding Processing

2000 ◽  
Author(s):  
Baojiu Lin ◽  
Won Gil Ryim
Keyword(s):  
Injection Molding ◽  
Simulation Software ◽  
Innovative Technology ◽  
Software Module ◽  
Location Optimization ◽  
Gate Location ◽  
Part Quality ◽  
Design Cycle ◽  
Injection Molding Simulation ◽  
Complex Models

Abstract Improvements in part quality and cost reduction are the primary objectives of CAE use in the injection molding industry. Engineers use advanced injection molding simulation software to analyze and verify their part designs. Traditionally, engineers have had to rerun simulations to verify the effects of changes in gate locations. For complex models, simulations are very time consuming. To reduce the design cycle time, a Design Optimization Module is developed by C-MOLD. One of the functions of this new software module is to automatically select optimal gate locations. This innovative technology is the result of close R&D collaboration between C-MOLD and LG-PRC in Korea. An overview of gate location optimization technology is presented in this paper, and several examples are also presented as illustration.

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