scholarly journals A multicriteria simulation optimization method for injection molding

2011 ◽  
Vol 31 (5) ◽  
Author(s):  
María G. Villarreal-Marroquín ◽  
Mauricio Cabrera-Ríos ◽  
José M. Castro
Keyword(s):  
Injection Molding ◽  
Design Of Experiments ◽  
Performance Measures ◽  
Simulation Optimization ◽  
Optimization Method ◽  
Efficient Solutions ◽  
Performance Measure ◽  
Injection Molding Process ◽  
Molding Process ◽  
Plastic Parts

Abstract Injection molding is the most important process for mass-producing plastic products. To help improve and facilitate the molding of plastic parts, advanced computer simulation tools have been developed. While modeling is complicated by itself, the difficulty of optimizing the injection molding process is that the performance measures involving the injection molding process usually show conflicting behaviors. Therefore, the best solution for one performance measure is usually not the best in some other performance measures. This paper introduces a simulation optimization method which considers multiple performance measures and is able to find a set of efficient solutions without having to evaluate a large number of simulations. The main components of the method are metamodeling, design of experiments, and data envelopment analysis. The method is illustrated and detailed here using a simple test example, and it is applied to a real injection molding case. The performance of the method using a different design of experiments is also discussed.

Selecting process parameter in injection molding via simulation optimization

2011 ◽  
Vol 31 (5) ◽  
Author(s):  
María G. Villarreal-Marroquín ◽  
Rachmat Mulyana ◽  
José M. Castro ◽  
Mauricio Cabrera-Ríos
Keyword(s):  
Injection Molding ◽  
Simulation Optimization ◽  
Mold Temperature ◽  
Optimization Method ◽  
Performance Measure ◽  
Melt Temperature ◽  
Process Variability ◽  
Composite Function ◽  
Automotive Part ◽  
Adaptive Metamodeling

Abstract A simulation optimization method based on design of experiments and adaptive metamodeling techniques is applied in this work to set process parameters in injection molding. The proposed method is used first to select the best processing conditions to injection molding a disposable camera front plate in the presence of either a single performance measure or a composite function of a series of performance measures. Secondly, it is used to select the best injection gate configuration from three different injection scenarios, as well as the values of mold temperature and melt temperature for a real automotive part in order to minimize process variability. The optimization results are discussed in light of the performance of the simulation optimization method.

Study on Improving the Life of Stereolithography Injection Mold

2012 ◽  
Vol 468-471 ◽  
pp. 1013-1016 ◽  
Author(s):  
Hua Qing Lai
Keyword(s):  
Injection Molding ◽  
Injection Molding Process ◽  
Injection Mold ◽  
Molding Process ◽  
Molded Parts ◽  
Injection Molded ◽  
Plastic Parts ◽  
Assembly Operations ◽  
Conventional Injection Molding ◽  
Shape And Size

Molding is one of the most versatile and important processes for manufacturing complex plastic parts. It is a method of fabricating plastic parts by utilizing a mold or cavity that has a shape and size similar to the part being produced. Molten polymer is injected into the cavity, resulting in the desired part upon solidification. The injection-molded parts typically have excellent dimensional tolerance and require almost no finishing and assembly operations. But new variations and emerging innovations of conventional injection molding have been continuously developed to offer special features and benefits that cannot be accomplished by the conventional injection molding process. This study aims to improving the life of stereolithography injection mold.

Optimization of the Injection Molding Process Parameters Based on Moldflow and Orthogonal Experiment

2013 ◽  
Vol 561 ◽  
pp. 239-243 ◽  
Author(s):  
Yong Nie ◽  
Hui Min Zhang ◽  
Jia Teng Niu
Keyword(s):  
Injection Molding ◽  
Orthogonal Experiment ◽  
Mold Temperature ◽  
Processing Parameters ◽  
Influential Factors ◽  
Injection Molding Process ◽  
Range Analysis ◽  
Molding Process ◽  
Melt Temperature ◽  
Plastic Parts

This article is using Moldflow analysis and orthogonal experimental method during the whole experiment. The injection molding process of motor cover is simulated under various technological conditions.After forming the maximum amount of warpage of plastic parts for evaluation.According to the range analysis of the comprehensive goal, the extent of the overall influence to the processing parameters, such as gate location, melt temperature, mold temperature and holding pressure is clarified.Through analyzing the diagrams of influential factors resulted from the simulation result,the optimized process parameter scheme is obtained and further verified by simulation.

Robust Design in Injection Molding Processing Based on Multi-Objective Ant Colonies Algorithm with Crossover and Variation

2011 ◽  
Vol 88-89 ◽  
pp. 279-284
Author(s):  
Feng Li Huang ◽  
Mei Peng Zhong ◽  
Jin Mei Gu ◽  
G.W. Liu
Keyword(s):  
Standard Deviation ◽  
Injection Molding ◽  
Robust Design ◽  
Injection Molding Process ◽  
Molding Process ◽  
Ant Colonies ◽  
Multi Objective ◽  
Plastic Parts ◽  
Crossover And Mutation ◽  
Plastic Injection

Based on single objective robust design of injection molding process, a bi-objective robust design model based on mean and standard deviation of molding quality and a multi-objective ant colonies algorithm with crossover and mutation based on Pareto optimization are proposed. Aimed at the craft parameters of plastic injection for the top and down shell of remote controller, a model of bi-objective robust design based on mean and standard deviation of warpage quantity is established with an example. And the model is solved by multi-objective ant colonies algorithm of crossover and mutation. The result shows that partial performances of algorithm are superior to that of NSGAII. The actual plastic injection was done by means of the parameters which were gotten by multi-objective robust optimization. The quality of plastic parts was high, and the fluctuation was small.

The Effect of Nano Hydroxyapatite Particles on Morphology and Mechanical Properties of Microcellular Injection Molded Polylactide/Hydroxyapatite Tissue Scaffold

2010 ◽  
Author(s):  
Adam Kramschuster ◽  
Lih-Sheng Turng ◽  
Wan-Ju Li ◽  
Yiyan Peng ◽  
Jun Peng
Keyword(s):  
Mechanical Properties ◽  
Injection Molding ◽  
Low Cost ◽  
Tissue Growth ◽  
Batch Processes ◽  
Injection Molding Process ◽  
High Porosity ◽  
Molding Process ◽  
Tissue Scaffold ◽  
Plastic Parts

The current large demands for transplant organs and tissues has led to extensive research on material synthesis and fabrication methods for biodegradable polymeric scaffolds, which are required to have high porosity, well interconnected pore structure, and good mechanical properties. However, the majority of current scaffold fabrication techniques are either for batch processes or use organic solvents, which can be detrimental to cell survival and tissue growth. The ability to mass produce solvent-free, highly porous, highly interconnected scaffolds with complex geometries is essential to provide off-the-shelf availability [1]. Injection molding has long been used for mass production of complex 3D plastic parts. The low-cost manufacturing, repeatability, and design flexibility inherent in the injection molding process make it an ideal manufacturing process to create 3D scaffolds, as long as high porosity and interconnectivity can be imparted into the finished product.

Injection Molding Process Parameter Optimization for Warpage Minimization Based on Uniform Design of Experiment

2010 ◽  
Vol 37-38 ◽  
pp. 570-575 ◽  
Author(s):  
Bao Shou Sun ◽  
Zhe Chen ◽  
Bo Qin Gu ◽  
Xiao Diao Huang
Keyword(s):  
Injection Molding ◽  
Design Of Experiment ◽  
Simulation Analysis ◽  
Uniform Design ◽  
Mold Temperature ◽  
Optimization Method ◽  
Processing Parameters ◽  
Injection Molding Process ◽  
Molding Process ◽  
Melt Temperature

To optimize injection molding warpage, this paper applies the uniform design of experiment method to search for the optimal injection molding processing parameters. The warpage. simulation analysis is accomplished by emplying Moldflow software. The melt temperature, mold temperature, injection time and packing pressure are regarded as processing parameters, and processing parameters are optimized through establishing a regression equation, and the optimization result and influence factors are analyzed. The results show that uniform design of experiment can reduce number of experiments used effectively and the quality of the product is greatly improved by the optimization method.

scholarly journals Optimization of injection molding process parameters based on GA-ELM-GA

2022 ◽  
Vol 355 ◽  
pp. 01029
Author(s):  
Yi Mei ◽  
Maoyuan Xue
Keyword(s):  
Genetic Algorithm ◽  
Injection Molding ◽  
Process Parameters ◽  
Orthogonal Experiment ◽  
Optimization Method ◽  
Injection Molding Process ◽  
Optimal Process ◽  
Range Analysis ◽  
Molding Process ◽  
Warpage Deformation

The most common optimization method for the optimization of injection mold process parameters is range analysis, but there is often a nonlinear coupling relationship between injection molding process parameters and quality indicators. Therefore, it is difficult to find the optimal process combination in range analysis. In this article, a genetic algorithm optimized extreme learning machine network model (GA-ELM) combined with genetic algorithm (GA) was proposed to optimize the process parameters of the injection mold. Take the injection molding process parameter optimization of an electrical appliance buckle cover shell as an example. In order to find the process parameters corresponding to the minimum warpage deformation, an orthogonal experiment was designed and the results of the orthogonal experiment were analyzed. Then, the corresponding optimal process combination and the degree of influence of process parameters on the warpage deformation were obtained. At the same time, the extreme learning machine network model (GA-ELM) optimized by the genetic algorithm was used to predict the warpage deformation of the plastic part. The trained GA-ELM model can map non-linear coupling relationship between the five process parameters and the warpage deformation well. And the optimal process parameters in the trained GA-ELM network model was searched by the powerful optimization ability of genetic algorithm. Generally speaking, the warpage deformation after optimization by range analysis is reduced by 6.7% compared with the minimum warpage after optimization by orthogonal experiment. But compared to the minimum warpage deformation after orthogonal experiment optimization, the warpage deformation after GAELM-GA optimization is reduced by 22%, which is better than that of the range analysis, thus verifying the feasibility and the optimization of the optimization method. This optimization method provides a certain theoretical reference and technical support for the field involving the optimization of process parameters.

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