薄壁塑件注塑成形特性的试验研究

设计制造了一可成形薄壁塑件的模具,利用正交试验方法(田口方法)进行充模试验,研究各工艺参数(注射速度、注射压力、熔体温度、注射量和模具温度等)对薄壁塑件注塑成形充模过程的影响。研究结果表明:模具温度对薄壁塑件的填充起决定性作用,注射压力和注射量是影响薄壁塑件成形的重要工艺参数,注射速度与熔体温度之间的交互作用对薄壁塑件成形的影响显著。     

超薄塑件注塑成形特性的试验研究与数值模拟

薄壁注塑成形技术具有节约材料、降低成本、减少制品重量和外形尺寸等优点,可促进移动电话等电子产品的迅速发展,特别是超薄塑件的注塑成形技术在微机电领域具有巨大的应用潜力。但随着制品厚度的减小也使注射成形难度加大,填充过程更为复杂,成形特性有待探索。设计制造出可成形超薄塑件的模具,利用正交试验方法(田口方法)进行充模试验和数值模拟技术研究各工艺参数(注射速度、注射压力、熔体温度、注射量和制品厚度等)对超薄塑件注塑成形充模过程的影响。研究结果表明,制品厚度对超薄塑件的填充起决定性作用;注射量及注射速度对超薄塑件注塑成形的填充起主导作用,提高注射速度能大幅度地提高填充率;熔体温度和注射压力相对于注射量和注射速度只起次要作用,但在填充过程中,高的熔体温度和注射压力也是必要的。     

Influence of molding conditions on the shrinkage and roundness of injection molded parts

During the plastic injection molding process, one of the biggest challenges is shrinkage which deteriorates the quality of produced parts. To control and reduce this defect, the essential way is to perfectly determine the variables like molding parameters. In this study, the effects of molding parameters including packing pressure, melt temperature, and cooling time on shrinkage and roundness have been investigated experimentally. Also, the relationship among initial molding parameters, the cavity pressure, and mold temperature was investigated. The results of this experimental study and analysis fulfill various requirements of plastic injection molding and clarify the relationship between molding conditions and the overall quality of produced parts. This study illustrated that packing pressure and melt temperature are dominant factors which determine the quality of parts.     

基于Moldflow的魔方中心轴注射分析与优化设计

应用Moldflow软件对魔方中心轴的注射成型过程进行浇口位置、充填、冷却和翘曲等模拟分析。通过在不同注射工艺条件下进行对比分析,确定了注射的最佳工艺参数:充填时间为2 s,注射+冷却时间为8 s,模具温度为40℃,熔体温度为240℃,注射压力为100 MPa。应用UG软件建立了注射模具的实体模型,解决了传统注射模具设计方法存在设计周期长、成本高且质量难以保证等问题。     

Optimization of injection molding process parameters using integrated artificial neural network model and expected improvement function method

In this study, an adaptive optimization method based on artificial neural network model is proposed to optimize the injection molding process. The optimization process aims at minimizing the warpage of the injection molding parts in which process parameters are design variables. Moldflow Plastic Insight software is used to analyze the warpage of the injection molding parts. The mold temperature, melt temperature, injection time, packing pressure, packing time, and cooling time are regarded as process parameters. A combination of artificial neural network and design of experiment (DOE) method is used to build an approximate function relationship between warpage and the process parameters, replacing the expensive simulation analysis in the optimization iterations. The adaptive process is implemented by expected improvement which is an infilling sampling criterion. Although the DOE size is small, this criterion can balance local and global search and tend to the global optimal solution. As examples, a cellular phone cover and a scanner are investigated. The results show that the proposed adaptive optimization method can effectively reduce the warpage of the injection molding parts.     

Minimization of sink mark depth in injection-molded thermoplastic through design of experiments and genetic algorithm

This paper deals with minimization of sink marks occurring behind the rib in plastic injection molding. In terms of rib structure and injection processing parameters, a theoretical analysis model was created. Meanwhile, finite element flow analysis with design of experiments (DOE) and genetic algorithm (GA) was integrated. Values of sink mark depth depend on design variables and technological parameters. Out of all, the four most influential variables, viz., rib thickness, mold temperature, melt temperature, and coolant temperature, were selected for optimization. The mathematic relation between sink mark depth and variables was established by conducting a set of FE analyses at various combinations of variables based on central composite design (CCD). Furthermore, the influence incidence of each factor and interaction between each variable on sink marks were investigated. The prediction model of sink marks was effectively coupled with GA for optimization of variables to minimize the sink depth. Results of the contrast analysis indicated that the proposed methodology could be used effectively in minimizing sink mark depth and parameter optimization design.     

Injection molding of polymer micro- and sub-micron structures with high-aspect ratios

This work studies the injection molding characteristics of polymer micro- and sub-micron structures using demonstration mold inserts with micro- and sub-micron channels with high-aspect ratios. The effects of the injection molding parameters on the achievable aspect ratio of the micro- and sub-micron walls were investigated. Additionally, distinctive mold-filling behaviors and resulting defects were observed for various polymers, such as polymethyl methacrylate (PMMA), polypropylene (PP) and high-density polyethylene (HDPE). Experimental results reveal that the mold temperature determines the success of the injection molding of micro- and sub-micron walls. The satisfactory mold temperature for micro-injection molding significantly exceeds that for traditional injection molding. Moreover, the main injection pressure and the main injection time substantially affect the achievable aspect ratio of the micro- and sub-micron walls. Furthermore, unusual flow behaviors occur and poor molding results are obtained when PP and HDPE are used for micro-injection molding.     

PLC在注塑机控制系统中的应用

SZ-250A型注塑机是一种中小型塑料注射成型机,它将颗粒状的塑料加热熔化到流动状,用注射装置快速、高压注入模腔,保压一定时间,冷却后成型为塑料制品。根据其工艺流程及工作控制要求,设计了以PLC为控制核心的控制系统,给出了此控制系统软硬件设计的全过程。通过实践使用证明,该控制系统具有快速、高效、高可靠性、抗干扰能力强等特点,实现了注塑机注塑全过程的自动控制。     

Mold design and forming process parameters optimization for passenger vehicle front wing plate

The main objective of the present article is to solve the problems of poor molding quality, large warpage, inadequate cooling effect and unsuitable selection of process parameters, in the injection molding process for passenger vehicle front-end plastic wing plate. The thickness and parting surface of the vehicle front-end fender were determined, the injection mold and its cooling system were designed. The relevant process parameters, affecting the product molding quality, were tested, according to orthogonal experimental approach, while their influence on the warpage was obtained, by analyzing the data. Finally, the BP neural network of warpage model was established and globally optimized using genetic algorithm. The optimal parameter combination of the injection molding process was derived as: melt temperature 236 °C, mold temperature 51 °C, cooling time 32 s, packing pressure 97 MPa and packing time 16 s.

     

An integrated parameter optimization system for MISO plastic injection molding

This paper presents the development of a parameter optimization system that integrates mold flow analysis, the Taguchi method, analysis of variance (ANOVA), back-propagation neural networks (BPNNs), genetic algorithms (GAs), and the Davidon–Fletcher–Powell (DFP) method to generate optimal process parameter settings for multiple-input single-output plastic injection molding. In the computer-aided engineering simulations, Moldex3D software was employed to determine the preliminary process parameter settings. For process parameter optimization, an L₂₅ orthogonal array experiment was conducted to arrange the number of experimental runs. The injection time, velocity pressure switch position, packing pressure, and injection velocity were employed as process control parameters, with product weight as the target quality. The significant process parameters influencing the product weight and the signal to noise (S/N) ratio were determined using experimental data based on the ANOVA method. Experimental data from the Taguchi method were used to train and test the BPNNs. Then, the BPNN was combined with the DFP method and the GAs to determine the final optimal parameter settings. Three confirmation experiments were performed to verify the effectiveness of the proposed system. Experimental results show that the proposed system not only avoids shortcomings inherent in the commonly used Taguchi method but also produced significant quality and cost advantages.     

基于Moldflow的薄壁件翘曲变形研究

翘曲变形是注塑件的主要缺陷,利用电器后盖对薄壁成型工艺进行研究。采用Moldflow软件对塑件成型过程进行数值模拟,研究了保压压力、塑件材料对注塑件翘曲变形的影响。对薄壁注塑件的数值仿真模拟结果进行统计分析,并且对影响注塑翘曲变形量的工艺参数进行综合分析,得到最优的工艺参数组合。研究结果表明:最佳的工艺参数组合可以使得塑件翘曲量变得最小。     

Analysis and modeling of effective parameters for dimension shrinkage variation of injection molded part with thin shell feature using response surface methodology

The injection molded housing part with thin shell feature could be produced to increase the internal space for packing more components. In this study, injection velocity, packing pressure, mold temperature, and melt temperature were selected as effective parameters for injection molding process. For the purpose of reducing dimension shrinkage variation of thin shell molded part, the response surface methodology was utilized to determine the relationship between input parameters and responses. Then the optimization condition was obtained according to the desirability function. Results show that melt temperature is the most significant factor on dimension shrinkage variation in transverse direction, followed by packing pressure, mold temperature, and injection velocity. However, in the longitudinal direction, packing pressure has the greatest influence on the dimension shrinkage variation, followed by injection velocity, melt temperature, and mold temperature. In accordance with verification experiments, the difference between the experimental data and predicted values ranges from ?9.8% to 1.8%. To obtain the optimal condition, the overall desirability must be larger than 0.9. Based on analysis of variance, the proposed models look reasonably accurate.     

基于Moldflow与正交试验法的注塑参数优化

在塑料产品的开发过程中,涉及到塑料模具进行注塑,注塑模具开发方案确定后,最重要的就是如何选择注塑参数。注塑参数可以在注塑机上直接进行试生产来调试,但必须是模具制造出来之后才能进行,对场地和设备均有要求,而且在试模过程中会浪费一定的塑料原材料。本文采用正交试验法对注塑参数进行优化,利用Moldflow软件的模具CAE技术对正交试验过程各种取值情况进行验证,并对最终优化组合进行验证,检验正交试验的正确性。确定翘曲变形量为实验指标,以注射温度、模具温度、充填时间、冷却时间、保压时间为变量的5因素,取各自允许取值范围进行4均分得到4水平,形成一个5因素4水平的正交试验矩阵设计实验,找出KDC-1型电磁断路器塑料壳体充填优化组合,通过在Moldflow的验证,及时反映了该正交试验结果是正确的注塑参数最优组合。     

基于Taguchi试验设计的储箱箱盖注射工艺参数研究

注射成型受众多因素影响,在制件结构和模具结构确定的条件下,通过合理的注射工艺参数,可消除或减少塑件成型中出现的缺陷。针对某企业在试生产一种储物箱箱盖时产生翘曲变形的问题,采用Taguchi试验方法,应用Moldflow对注射过程进行模拟,获得了塑件在熔料温度、模具温度、注射时间和保压压力四因素三水平下成型的翘曲变形量。采用极差分析,比较了不同工艺参数对翘曲变形量的影响程度,得到了优化的工艺参数组合。经试验验证,其效果良好,产品的翘曲变形得到了一定的改善。     

CAE技术在注塑成型浇注系统优化设计中的应用

注塑模浇注系统是塑料注塑成型模具设计中的关键技术之一,利用CAE软件Moldflow可对不同浇口位置进行流动模拟分析,预测可能存在的气泡和熔接痕的位置,为模具设计人员优化模具设计提供依据,提高一次试模的成功率。并经过实践证明,注塑成型中通过浇注系统位置的优化可以显著提高产品的质量。     

齿轮齿条斜抽芯机构注塑模设计

根椐塑料垫的结构特点,设计了由对称布置在模具内部的四组齿轮齿条斜抽芯机构、推杆推出机构等主要部分组成的四型腔单分型面注塑模。介绍了注塑模主要零件的结构设计,注塑机的选择,模具的校核和工作原理。设计的模具结构紧凑、合理,工作可靠。     

基于DOE技术的薄壁塑件翘曲变形工艺优化

文中在薄壁注射成型中将CAE技术和DOE(design ofexperiment)相结合,以薄壁盖板塑件为例,利用Moldflow对各工艺参数进行注射成型模拟分析。通过分析塑件翘曲变形的原因,得出保压压力对翘曲变形起主导性作用。并在正交试验的指导下优化工艺参数,有效降低塑件的翘曲变形。     

塑料压力盖模具设计与制造

本设计为塑料压力盖模具设计,介绍了压力盖注射模的结构及工作过程,着重介绍了一种新颖的采用斜导柱驱动方法进行侧向抽芯机构的结构设计,并阐述了该模具的工作过程,介绍了注射模设计中采用的强制脱模、滑动型延时顶出机构。涉及到注射机各种参数的选取、零部件的加工方法、注射模的结构及相关的计算问题、特种加工工艺及塑料的回收和利用等方面内容。     

基于神经网络和遗传算法的薄壳件注塑成型工艺参数优化

建立基于神经网络和遗传算法并结合正交试验的薄壳件注塑成型工艺参数优化系统.正交试验法用来设计神经网络的训练样本,人工神经网络有效创建翘曲预测模型;遗传算法完成对影响薄壳塑件翘曲变形的工艺参数(模具温度、注射温度、注射压力、保压时间、保压压力和冷却时间等)的优化,并计算出其优化值.按该参数进行试验,效果良好,可以有效地减小薄壳塑件翘曲变形,其试验数值与计算数值基本相符,说明所提出的方法是可行的.     

Simulation and Experiment on Workability for Cold Pressure Forming of Sheet Metal Part with Step Cross-section

In modem manufacturing, a new type of sheet metal part with step cross-section in both inner hole and outer edge is proposed. The traditional stamping separating processes can only produce sheet metal part with vertical cross-section. According to the latest developing theory and potential of cold pressure forming: combination of pressure and cold forging, a new flow control forming of sheet metal(FCF) is excogitated based on blanking process of general stamping and combined with cold forging processes such as extrusion and coining, etc, which is aiming at the above-mentioned new type of sheet metal part. With utilization of this new process, the new type of sheet metal parts can be manufactured. In order to shorten the testing period, the numerical simulation was carried out by using DEFORM-3D software, and both deformation and mechanics rules were analyzed. Based on the simulation, both punching part and blanked parts of this new type were successfully developed. Then a new conception of optimal distance between the step walls of inner hole and outside edge was proposed and the design principle for its numerical value was inferred. Furthermore, a mold set for combination of stamping & cold forging was designed and manufactured, by which the technologic experiments were taken for validation with Aluminum plate of thickness 2.35 mm for power battery cover board, which verified the principle of the distance between the step walls. The research of cold pressure forming of thin sheet metal with step cross-section is significant, not only to the development of modem mechanical manufacture, but also to metal plastic forming science.