Thermal and Design Sensitivity Analyses for Cooling System of Injection Mold, Part 2: Design Sensitivity Analysis

1998 ◽  
Vol 120 (2) ◽  
pp. 296-305 ◽  
Author(s):  
S. J. Park ◽  
T. H. Kwon
Keyword(s):  
Cooling System ◽  
Boundary Integral Equations ◽  
Volumetric Flow Rate ◽  
Design Sensitivity ◽  
Boundary Integral ◽  
Sensitivity Analyses ◽  
Bulk Temperature ◽  
Injection Molding Process ◽  
Cooling Channel ◽  
Molding Process

DSA will ultimately play an important role in the design optimization process. Part 2 of this paper presents an efficient and accurate methodology for the DSA of the cooling stage of the injection molding process. The DSA program developed in the present study utilizes the implicit differentiation of the boundary integral equations and the B.C.s presented in Part I with respect to all DVs to yield the sensitivity equations. In this DSA, we have considered various DVs as follows: (i) (DVs related to processing conditions) inlet coolant bulk temperature and inlet coolant volumetric flow rate of each cooling channel inlet, and (ii) (DVs related to mold cooling system design) radius and location of each cooling channel. Two sample problems are solved to demonstrate the accuracy and efficiency of the present DSA formulation and to discuss the characteristics of each DV.

Thermal and Design Sensitivity Analyses for Cooling System of Injection Mold, Part 1: Thermal Analysis

1998 ◽  
Vol 120 (2) ◽  
pp. 287-295 ◽  
Author(s):  
S. J. Park ◽  
T. H. Kwon
Keyword(s):  
Thermal Analysis ◽  
Injection Molding ◽  
Cooling System ◽  
Design Sensitivity ◽  
Sensitivity Analyses ◽  
Injection Molding Process ◽  
Molding Process ◽  
Exterior Surface ◽  
Cad System ◽  
Thermal Analysis Result

In recent years, increased attention has been paid to the design of cooling systems in injection molding, as it becomes clear that the cooling system affects significantly both productivity and part quality. In designing the cooling system of a mold efficiently in terms of rapid and uniform cooling, it would be desirable for mold designers to have an optimal CAD system. For this optimal design, one needs capabilities of both a thermal analysis (to be discussed in Part 1) and a corresponding DSA (to be presented in Part II) for the 3-d mold heat transfer during the cooling stage of an injection molding process. It was found that seemingly negligible inaccuracy in the thermal analysis result sometimes leads to meaningless DSA result. With a successful DSA being an intermediate goal towards optimum design, we have improved the thermal analysis system based on the modified BEM in terms of accuracy and developed rigorous treatments of B.C.s appropriate for DSA by considering the following issues: (i) numerical convergency, (ii) the series solution in part thermal analysis, iii) treatment of tip surface of line elements, (iv) treatment of coolant, and (v) treatment of mold exterior surface. Using two examples, this paper amply demonstrates the importance of these issues.

Study on the Flow Behavior in Thin Cavity during Water-Assisted Injection Molding

2011 ◽  
Vol 467-469 ◽  
pp. 80-83
Author(s):  
Tang Qing Kuang ◽  
Kun Han
Keyword(s):  
Injection Molding ◽  
Control Volume ◽  
Fluid Model ◽  
Flow Behavior ◽  
Experimental Result ◽  
Bulk Temperature ◽  
Injection Molding Process ◽  
Molding Process ◽  
Injection Location ◽  
Good Agreement

A numerical simulation model for the flow behavior of fluids in thin cavity during water assisted injection molding process is built up by adopting general Newtonian fluid model for the filling stage and non-Newtonian and compressible fluid model for the packing stage separately. Finite element/finite difference/control volume methods are adopted for the simulation of melt front, pressure variation at injection location, water thickness fraction and bulk temperature about a plate with trapezoidal cross-section. The simulated melt front location and shape have good agreement with experimental result. In comparison with the simulation results of conventional injection molding, it turns out that water assisted injection molding can obtain parts with low pressure requirement, perfect surface quality and rapid cooling.

Design and Simulation of Injection Mold for the Shell of Switch

2010 ◽  
Author(s):  
Chuanyang Wang ◽  
Shuai Hu ◽  
Qiubo Qian ◽  
Xuanxuan Shen
Keyword(s):  
Simulation Analysis ◽  
Cooling System ◽  
Injection Pressure ◽  
3D Models ◽  
Injection Molding Process ◽  
Injection Mold ◽  
Molding Process ◽  
Development Cycle ◽  
Successful Probability ◽  
Filling Time

The 3D models of gating system, ejection mechanisms and cooling system of the swtich shell for injection mold are designed by using Pro/ENGINEER software. MOLDFLOW is utilized for CAE analysis. Three schemes are obtained by changing the gate location during the injection molding process. After comparing the volume shrinkage during injection, shrink marks index, filling time and the injection pressure, the best scheme is obtained. According to the optimal scheme, the injection mold is designed. The results showed that simulation analysis method can not only improve the successful probability of mold trial, but also shorten the production development cycle of developing product.

scholarly journals Application of Intelligent Modeling Method to Optimize the Multiple Quality Characteristics of the Injection Molding Process of Automobile Lock Parts

Polymers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2515
Author(s):  
Wei-Tai Huang ◽  
Chia-Lun Tsai ◽  
Wen-Hsien Ho ◽  
Jyh-Horng Chou
Keyword(s):  
Temperature Distribution ◽  
Injection Molding ◽  
Process Parameters ◽  
Cooling System ◽  
Injection Molding Process ◽  
Molding Process ◽  
Conformal Cooling ◽  
Characteristic Index ◽  
Average Temperature ◽  
Gray Correlation

This study focuses on applying intelligent modeling methods to different injection molding process parameters, to analyze the influence of temperature distribution and warpage on the actual development of auto locks. It explores the auto locks using computer-aided engineering (CAE) simulation performance analysis and the optimization of process parameters by combining multiple quality characteristics (warpage and average temperature). In this experimental design, combinations were explored for each single objective optimization process parameter, using the Taguchi robust design process, with the L18 (21 × 37) orthogonal table. The control factors were injection time, material temperature, mold temperature, injection pressure, packing pressure, packing time, cooling liquid, and cooling temperature. The warpage and temperature distribution were analysed as performance indices. Then, signal-to-noise ratios (S/N ratios) were calculated. Gray correlation analysis, with normalization of the S/N ratio, was used to obtain the gray correlation coefficient, which was substituted into the fuzzy theory to obtain the multiple performance characteristic index. The maximum multiple performance characteristic index was used to find multiple quality characteristic-optimized process parameters. The optimal injection molding process parameters with single objective are a warpage of 0.783 mm and an average temperature of 235.23 °C. The optimal parameters with multi-objective are a warpage of 0.753 mm and an average temperature of 238.71 °C. The optimal parameters were then used to explore the different cooling designs (original cooling, square cooling, and conformal cooling), considering the effect of the plastics temperature distribution and warpage. The results showed that, based on the design of the different cooling systems, conformal cooling obtained an optimal warpage of 0.661 mm and a temperature of 237.62 °C. Furthermore, the conformal cooling system is smaller than the original cooling system; it reduces the warpage by 12.2%, and the average temperature by 0.46%.

Machine Learning Aided Design and Optimization of Conformal Porous Structures

2020 ◽  
Author(s):  
Zhenyang Gao ◽  
Danièle Sossou ◽  
Yaoyao Fiona Zhao
Keyword(s):  
Machine Learning ◽  
Cooling System ◽  
Design Parameters ◽  
Injection Molding Process ◽  
Porous Structures ◽  
Molding Process ◽  
Cooling Performance ◽  
Temperature Variance ◽  
Design And Optimization ◽  
Aided Design

Abstract The porous cooling system has been proved to have significant advantages over traditional 2D conformal cooling channels due to its rapid cooling performance during the injection molding process. Compared to conventional porous systems, the conformal porous structures (CPS) have been proven to have even more uniform cooling performance and a reduced temperature variance of the part. For the part with unevenly distributed thickness values however, the temperature variance problem remains unsolved. In addition, there is a lack of modeling and optimization efforts on developing an optimal CPS structure with varying cooling cell sizes to achieve better cooling performances. To solve this problem, a machine learning approach is applied to predict the part surface temperature based on identified CPS design parameters. With this surrogate temperature prediction model, the optimization is performed to generate a machine learning aided design of CPS. The simulation results of a swimming pedal case study indicate that the machine learning aided CPS is able to achieve a 76% reduction in temperature variance compared to conventional CPS.

Computer Simulation of Warpage Formation in Polymer Injection Molding of a Step Pad

2006 ◽  
Author(s):  
Sridhar P. Ramamurthy ◽  
Lyle Steenson ◽  
Zhong Hu
Keyword(s):  
Injection Molding ◽  
Cooling System ◽  
Three Dimensional ◽  
Nonlinear Material ◽  
Injection Molding Process ◽  
Molding Process ◽  
Element Analysis ◽  
Polymer Injection ◽  
Fea Model ◽  
Polymer Injection Molding

Warpage is one of the most common defects of a plastic product in the polymer injection molding process. It is attributed to the differential shrinkage after the part is ejected from the die cavity due to the nonlinear material property of the polymer, improper design of the cooling system, geometry of the part and the related process parameters. In this paper, the warpage formation of a plastic part, Step Pad of polypropylene copolymer, in the cooling stage of the polymer injection molding process was simulated by finite element analysis (FEA). A three-dimensional FEA model, taking into account the nonlinear material (polypropylene copolymer) properties, with a thermal-structural sequential coupled approach of higher computing efficiency was developed. The effects of mold closed time and layout of cooling system on the dimension and shape of the part were investigated. Industrial experiments for the different mold closed times (25s, 30s, 35s, 40s, 45s, 50s, and 55s) were conducted. The simulation results were compared with the experimental results. The approach is effective in predicting warpage in the polymer injection molding processes.

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