Expert System of Precise Injection Molding Process Optimization Based on Moldflow Software

2009 ◽  
Vol 87-88 ◽  
pp. 451-455
Author(s):  
Peng Cheng Xie ◽  
Bin Du ◽  
Zhi Yun Yan ◽  
Yu Mei Ding ◽  
Wei Min Yang
Keyword(s):  
Expert System ◽  
Injection Molding ◽  
Process Optimization ◽  
Weld Line ◽  
Injection Molding Process ◽  
Molding Process ◽  
Set Up ◽  
And Control

An expert system of precise injection molding process optimization based on Moldflow software was set up in this paper. Expert system of precise injection molding process optimization based on Moldflow-MPI module consist of optimization of packing curve, analyzer of parallelism and coaxiality, analyzer of process optimization and integrative forecaster of weld line. The system can be used in the process optimization of precise injection molding, the forecast and control of product properties, and the flaw elimination of product molding.

Injection Molding Process Optimization of Multi-Objective Based on MUD-RBFNN-GA

2010 ◽  
Vol 37-38 ◽  
pp. 564-569
Author(s):  
Bao Shou Sun ◽  
Zhe Chen ◽  
Bo Qin Gu ◽  
Xiao Diao Huang
Keyword(s):  
Injection Molding ◽  
Process Optimization ◽  
Simulation Analysis ◽  
Weld Line ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature ◽  
Multi Objective ◽  
Uniform Designs ◽  
Moldflow Simulation

The optimization algorithm of MUD-RBFNN-GA was proposed in this article. An injection molding process optimization model of multi-factor and multi-objective was also researched. The multiple uniform designs of experiment was applied to optimize the processing parameters. During this process, the RBF neural network was established, where the melt temperature, mold temperature and packing pressure were taken as the inputs, and warpage, area of air-traps and weld-line length as the outputs, and the Moldflow simulation analysis was used to obtain the output values. By combining the algorithm with genetic algorithm and global optimization in the networks, we can get the optimal process parameters. The results show that the multi-objective optimization based on MUD-RBFNN-GA is practically applicable, and it can reduce the molding defects effectively.

Reduction of Rejection Rate for High Gloss Plastics Product Using Six Sigma Method

2014 ◽  
Vol 606 ◽  
pp. 141-145
Author(s):  
Che Ku Abdullah Che Ku Kairulazam ◽  
M.I. Hussain ◽  
Zuraidah Mohd Zain ◽  
Nabilah A. Lutpi
Keyword(s):  
Injection Molding ◽  
Six Sigma ◽  
Rejection Rate ◽  
Injection Molding Process ◽  
Molding Process ◽  
Sigma Level ◽  
Potential Factors ◽  
High Rejection Rate ◽  
And Control ◽  
Plastic Injection

High gloss plastics part in injection molding industries were widely used in Malaysia. However the high rejection rate in this industries were major problem affecting the economic aspects. Therefore this paper presents an approach of implementing six sigma method to reduce the rejection rate in a plastic injection molding process for high gloss plastics part. Define, Measure, Analyze Improve and Control (DMAIC) methodology was applied as basis of the study. By using current process, the average of rejection is 40.6% and the aim of this study is to reduce the rejection rate to less than 10 % . All potential factors were taken into account to identify the significant factors. The improvement process was made base on the analysis output. This study was successful with increment in sigma level from 1.74 σ to 3.00 σ. .

scholarly journals Intelligent Injection Molding on Sensing, Optimization, and Control

2020 ◽  
Vol 2020 ◽  
pp. 1-22 ◽  
Author(s):  
Peng Zhao ◽  
Jianfeng Zhang ◽  
Zhengyang Dong ◽  
Junye Huang ◽  
Hongwei Zhou ◽  
...  
Keyword(s):  
Injection Molding ◽  
Control Strategies ◽  
Research Field ◽  
Future Research ◽  
Injection Molding Process ◽  
Molding Process ◽  
Geometric Precision ◽  
Optimization And Control ◽  
Active Research ◽  
And Control

Injection molding is one of the most significant material processing methods for mass production of plastic products. It is widely used in various industry sectors, and its products are ubiquitous in our daily life. The settings and optimization of the injection molding process dictate the geometric precision and mechanical properties of the final products. Therefore, sensing, optimization, and control of the injection molding process have a crucial influence on product quality and have become an active research field with abundant literature. This paper defines the concept of intelligent injection molding as the integral application of these three procedures—sensing, optimization, and control. This paper reviews recent studies on methods for the detection of relevant physical variables, optimization of process parameters, and control strategies of machine variables in the molding process. Finally, conclusions are drawn to discuss future research directions and technologies, as well as algorithms worthy of being explored and developed.

Application of Optimization Algorithms in Injection Molding Process Parameters Optimization

2011 ◽  
Vol 704-705 ◽  
pp. 183-190
Author(s):  
Ze Hao Hu ◽  
Wei Wei ◽  
Juan Liu ◽  
Kun Liu
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Design Method ◽  
Orthogonal Experiment ◽  
Parameters Optimization ◽  
Injection Molding Process ◽  
Molding Process ◽  
Bp Artificial Neural Network ◽  
Agent Model ◽  
Set Up

In this paper, the numerical simulation and calculation of injection molding process are taken in the Moldflow software. The BP artificial neural network combining with the orthogonal experiment design method is used to set up the injection molding process agent model, genetic algorithms are applied to realize global optimization, finally, the optimal combination of process parameters of each quality indicators is obtained.

scholarly journals Design of Multimodel based MPC and IMC control schemes applied to injection molding machine

2014 ◽  
Vol 3 (2) ◽  
pp. 82
Author(s):  
Kanaga Lakshmi ◽  
D. Manamalli ◽  
M. Mohamed Rafiq
Keyword(s):  
Injection Molding ◽  
Temperature Control ◽  
Weighted Average ◽  
Injection Molding Process ◽  
Monitoring And Control ◽  
Molding Machine ◽  
Molding Process ◽  
Melt Temperature ◽  
Injection Molding Machine ◽  
And Control

Good control of plastic melt temperature for injection molding is very important in reducing operator setup time, ensuring product quality, and preventing thermal degradation of the melt. The controllability and set points of barrel temperature also depend on the precise monitoring and control of plastic melt temperature. Motivated by the practical temperature control of injection molding, this paper proposes MPC and IMC based control scheme. A robust system identification and control methodology is developed which uses canonical varieties analysis for identification and model predictive control for regulation. The injection molding process consists of three zones and the mathematical model for each of the zone is different. The control output for each zone controller is assigned a weight based on the computed probability of each model and the resulting action is the weighted average of the control moves of the individual zone controllers. Keywords: Injection-Molding Machine (IMM), IMC Control, Temperature Control.

A Study of Ceramic Injection Molding of Watch Case Composed of ZrO2 Powder

2007 ◽  
Vol 534-536 ◽  
pp. 337-340 ◽  
Author(s):  
Te Su Kwak
Keyword(s):  
Computer Simulation ◽  
Injection Molding ◽  
Flow Pattern ◽  
Ceramic Powder ◽  
Weld Line ◽  
Powder Injection Molding ◽  
Powder Injection ◽  
Injection Molding Process ◽  
Molding Process ◽  
Inertia Effects

This study is focused on the manufacturing technique of powder injection molding of watch case made from zirconia powder. A series of computer simulation processes were applied to the prediction of the flow pattern in the inside of the mould and defects as weld-line. The material properties of melted feedstock, including the PVT graph and thermal viscosity flowage properties were measured to obtain the input data to be used in a computer simulation. Also, a molding experiment was conducted and the results of the experiment showed a good agreement with the simulation results for flow pattern and weld line location. On the other hand, gravity and inertia effects have an influence on the velocity of the melt front because of the high density of ceramic powder particles during powder injection molding in comparison with polymer’s injection molding process. In the experiment, the position of the melt front was compared with the upper gate and lower gate positions. The gravity and inertia effect could be confirmed in the experimental results.

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