微齿轮注塑成型正交优化及数值模拟

介绍了采用高聚物成型微齿轮的主要成型方法--微注射成型.比较了不同种类的注射原料ABS、聚丙烯(PP)、聚碳酸酯(PC)的成型工艺,并就影响微注射成型中影响微制件质量的主要工艺过程:充模压力、熔体温度、模具温度和充填时间等进行数值模拟研究,采用正交优化方法对成型方案进行优化,获得优化的成型参数.为微齿轮成型模具的结构设计、成型工艺参数的合理化等等提供理论依据.通过对微齿轮成型过程的数值模拟优化,得到微注射成型的模具温度升高、注射压力增大、注射温度升高都会缩短充模时间;结果显示,聚合物材料对微注塑齿轮的适用性依次为:ABS＞PP＞PC.     

基于翘曲的注塑成型工艺参数优化组合

采用Taguchi方法设计注塑成型模拟实验,以注塑成型工艺参数混合优化模块方法确定工艺参数最优组合。先建立注塑成型工艺参数混合优化模块,按L9(34)正交表进行实验,得到熔体温度、保压压力、注射时间、成型周期时间等参数不同水平时的翘曲和收缩率数据,翘曲量和收缩率都属于望小特性,计算出S/N比,通过S/N比反应图分析得出较优工艺参数组合,再实验验证确定最优组合,最后说明注塑成型工艺参数混合优化模块方法可行。     

基于多域正交空间协同演进的薄壁注塑件翘曲优化研究

目的 鉴于细长、异形、薄壁注塑件成型机理复杂,且容易产生翘曲变形,以及传统工艺优化方法存在局限性的问题,以某轿车薄壁件为研究对象,优化注射成型工艺,以实现降低翘曲变形,提高效率的目的。方法 首先,对压力、温度因素及多重效应造成细长、异形、薄壁注塑件翘曲变形的机理进行分析。然后,在正交试验设计的基础上,应用Moldflow软件模拟仿真获取数据,并进行方差分析,获得各工艺参数的显著性。为了进一步优化工艺参数,打破传统优化方法存在的局限,提出一种多域正交空间协同演进(MDOSE)的集成优化方法。最后,基于该方法优化某轿车薄壁件的翘曲变形,并将其应用于实际生产制造。结果 与初始试验方案相比,优化后制件z方向上的翘曲从1.022 mm降低到了0.085 7 mm,减小了91.6%,证实了MDOSE优化方法的有效性和实用性。结论 优化结果表明,MDOSE优化方法一定程度上解决了薄壁件的翘曲优化问题,改善了传统工艺优化方法的局限。机理分析和工艺方法为往后的薄壁注塑件的实际生产提供了一定的理论支撑。     

聚合物微流控芯片的注射成型

针对注塑成型微流控芯片过程中出现翘曲变形和微通道复制精度不高等缺陷,采用正交分析法,仿真优化了芯片厚度方向上的翘曲变形;基于翘曲优化结果,实验研究了微注射成型微流控芯片过程中模具温度、熔体温度和注射速度对微通道变形的影响。结果表明,保压时间和保压压力对微流控芯片的翘曲变形影响最大,而模具温度对微通道变形影响最为显著。采用优化的工艺参数,所成型的芯片微通道具有较高的复制度,无明显翘曲变形,可满足使用要求。     

微注射浇注系统对微制件熔接缝形成的影响的模拟研究

微塑件的需求逐年增加,微注射是批量生产高精度微塑件的主要手段,但与宏观注射方法相比,制件尺寸的微小化也给微注射在理论、工艺、设备、检测等方面带来了难题.浇注系统、熔接缝的位置和数目是影响微制件质量的主要因素,本工作就此进行了数值模拟,得出了微成型与传统注射成型工艺参数的差异.结果表明:微注射成型的温度、压力和速度均高于传统注射成型,微注射成型过程中温度是保证微注射能否顺利进行的关键,微注射成型的模具温度必须高于聚合物材料的玻璃化转变温度,因此对微注射成型必须进行有效温控.     

微注射成型研究进展

微注射成型是一种低成本大规模复制聚合物微制件的有效方法。文中从微结构特征复制性能、工艺参数的分析和优化、模具表面光洁度对聚合物流动行为的影响、过程建模与仿真、微注射成型的熔接痕缺陷以及微塑件的组织形态与力学性能等方面阐述微注射成型的最新研究进展。最后指出开发特殊微注射成型技术、新型微模具加工技术,以及将微注射成型与其他微纳加工技术集成,制作多种材料复杂功能微系统将成为今后的研究方向和发展趋势。     

注射工艺参数对PC/ABS材料制品收缩与翘曲的影响

将计算机模拟注射成型过程和实验优化设计相结合,提供了一套经济有效便捷的方法对各工艺参数进行定量的统计分析。选用L27(3^13)正交表设计实验,通过研究注射速率来判断流动引起的收缩;计算模具温度、熔体温度、保压压力与保压时间来确定热诱导的收缩;研究浇口尺寸来判断剪切热对PC／ABS塑料制品收缩的影响程度。以洗衣机上盖为例,以Taguchi实验方法为设计准则安排CAE分析,在制品关键部位采集收缩翘曲量,通过对因素与水平进行的方差分析和直观分析,最后得出熔体温度和保压压力对PC／ABS塑料制件的收缩翘曲影响最大。     

考虑气指效应的气辅成型穿透行为的工艺优化

以气体穿透相对深度和气指高度作为评价指标来研究气体辅助注射成型中的气体穿透行为,采用Kriging代理模型建立上述两指标与气辅成型工艺参数制件的近似拟合关系,并采用自适应粒子群算法(APSO)进行全局寻优。其中最大气指高度将通过罚函数方法转化为约束条件。应用所建立的优化方案对某汽车车门气辅制件的工艺参数进行优化。算例表明,上述方案优化效果明显,且具有精度高、收敛速度快的特点。     

工艺参数对短玻璃纤维增强PP复合材料注射压力和翘曲变形的影响

采用Moldflow对聚丙烯及其短玻璃纤维增强复合材料的注塑成型过程进行3D模拟分析,基于Taguchi试验设计方法(DOE),采用L16(45)正交矩阵进行试验设计,研究工艺参数对注射压力和翘曲变形的影响。结果表明,纤维含量对注射压力和翘曲变形影响作用较为显著,且存在最佳值;模具温度、熔体温度、保压时间和保压压力对注射压力的影响为单调的线性关系,但其对翘曲变形的影响较复杂。     

注塑成型制品翘曲变形优化建模分析

目的 针对传统建模方法在预测的翘曲变形位置与实际偏差较大的问题,开展基于Moldflow的注塑成型制品翘曲变形优化建模分析研究.方法 通过数据模拟分析预处理、浇注体系模型构建、基于Moldflow的注塑成型制品翘曲变形过程模拟等手段,实现对注塑成型制品曲面参数优化.结果 通过对比实验证明,新的建模方法与传统建模方法相比...     

基于混沌粒子群的微齿轮注塑精密成形翘曲变形分析

目的 针对注塑加工生产的微齿轮运转一段时间后会出现严重变形的问题,对微齿轮注塑精密成形翘曲变形进行分析。方法 基于混沌粒子群建立微齿轮注塑CAE模型,获取曲面全局最优解,在此基础上,计算微齿轮注塑精密成形翘曲收缩率,得到翘曲变形量,同时优化微齿轮注塑精密成形工艺参数,分析微齿轮注塑精密成形翘曲变形情况。结果 将仿真结果与实际试验结果进行对比,得出该分析方法的预测结果与实际翘曲变化趋势完全一致。结论 微齿轮注塑中心位置的翘曲变形量最大,离中心位置越远,翘曲变形量越小。     

Residual stress development during the composite patch bonding process: measurement and modeling

This paper presents an experimental technique for monitoring residual stress development throughout the composite patch repair curing process. Using this technique, process-induced strains and specimen warpage during a number of different cure cycles were measured for a simulated single-sided composite patch repair of an aluminum substrate. Models for adhesive cure rate and glass transition behavior of the patch adhesive resin (FM 300-1K) were combined with a simple bi-metallic strip model to predict specimen warpage and strain behavior during cure. Model predictions were compared with experimental measurements and were used to assist in the development of optimized cure cycles. Using these optimized cycles, it was found that it was possible to achieve significant (>20%) reductions in patch warpage and at the same time, minimize processing time and obtain a high final adhesive degree of cure. Experimental observations suggest that an improved patch model incorporating adhesive viscoelastic behavior during cure would assist in achieving additional process improvements.     

基于代理模型和改进遗传算法的注塑翘曲优化

提出一种最小化制品翘曲的注塑工艺参数优化集成方法.以空调柜机顶盖注塑制品开发为例,该方法使用Moldflow软件分析制品的翘曲变形,运用田口方法确定与制品翘曲量密切相关的工艺因素,然后采用响应曲面法(RSM)和改进的精英保留自适应遗传算法(EAGA)相结合的方法,建立主要影响工艺参数与制品翘曲量之间的关系模型,通过对模型寻优以实现对制品翘曲的优化.该方法的适用性在制品的实际生产中得到了验证.     

Research on the reduction of sink mark and warpage of the molded part in rapid heat cycle molding process

Rapid heat cycle molding (RHCM) is a recently developed innovative injection molding technology to enhance the surface quality of the plastic parts without extending the molding cycle. Most of the common defects that occur in the plastic parts produced by conventional injection molding (CIM), such as flow mark, silver mark, jetting mark, weld mark, exposed fibers, short shot, etc., can be well solved by RHCM. However, RHCM is not a nostrum for all the defects in injection molding. Sink mark and warpage are two major defects occurring in RHCM. The purpose of this study is to investigate and further solve the sink mark and warpage of the molded parts in RHCM. To solve the problem of sink mark, a new “bench form” structure for the screw stud on the product coupling with a lifter structure for the injection mold was proposed. The external gas assisted packing was also proposed to reduce the sink mark in RHCM. To solve the problem of warpage, design of experiments via Taguchi methods were performed to systematically investigate the effect of processing parameters including melt temperature, injection time, packing pressure, packing time and also cooling time on the warpage. Injection molding simulations based on Moldflow were conducted to acquire the warpages of the plastic parts produced under different processing conditions. A signal to noise analysis was conducted to analyze the effect of the factors, and the optimal processing parameters were also found out. ANOVA was also conducted to quantitatively analyze the percentage contributions of the processing parameters on the warpage. The verification results show that part warpage can be reduced effectively based on the optimal design results.     

Back Propagation neural network modeling for warpage prediction and optimization of plastic products during injection molding

Warpage of plastic products is an important evaluation index for Plastic Injection Molding (PIM). A Back Propagation (BP) neural-network model for warpage prediction and optimization of injected plastic parts has been developed based on key process variables including mold temperature, melt temperature, packing pressure, packing time and cooling time during PIM. The approach uses a BP neural network trained by the input and output data obtained from the Finite Element (FE) simulations which are performed on Moldflow software platform. In addition, a kind of automobile glove compartment cap was utilized in this study. Trained by the results of FE simulations conducted by orthogonal experimental design method, the prediction system got a mathematical equation mapping the relationship between the process parameter values and warpage value of the plastic. It has been proved that the prediction system has the ability to predict the warpage of the plastic within an error range of 2%. Process parameters have been optimized with the help of the prediction system. Meanwhile energy consumption and production cycle were also taken into consideration. The optimized warpage value is 1.58 mm, which is shortened by 32.99% comparing to the initial warpage result 2.358 mm. And the cooling time has been decreased from 20 s to 10 s, which will greatly shorten the production cycle. The final product can satisfy with the matching requirements and fit the automobile glove compartment well.     

A hybrid inverse method for evaluating FC-PBGA material response to thermal cycles

This study proposes a hybrid experimental-analytical inverse method that can be used to evaluate thermomechanical cyclic behavior of flip-chip plastic ball grid array modules and the constituent materials. Treating such a package as an adhesively bonded trilayer plate, the structural formulation follows and modifies an existing analytical model. A phase-shifted shadow moiré method is employed to obtain the package thermal warpage variation in responding to a temperature cycle. By correlating the modeling predicted and the experimentally measured package warpage, the application of the method leads to the determination of those uncertain material parameters including temperature dependent modulus of elasticity and coefficient of thermal expansion of the die attachment and the substrate materials. These parameters are difficult to determine otherwise due to the complexity involving the effect of package processing condition and extremely thin thickness of the adhesive layer. As the values of all material parameters are ascertained, shear and peel stresses in the module adhesive layer can also be evaluated based on the analytical model.     

Experimental study of warpage and shrinkage in injection molding of HDPE/rPET/wood composites with multiobjective optimization

In this paper, injection molding of squared parts with 1.25 mm in thickness, composed of wood plastic composites (high-density polyethylene, recycled polyethylene terephthalate, and wood flour), was done. The warpage and volumetric shrinkage in the parts was determined experimentally with various process conditions (packing time, melt temperature, wood content, and packing pressure). The experiments were done based on Box–Behnken design of experiments. The significance of each parameter and model was evaluated by analysis of variance (ANOVA). ANOVA showed that packing time and melt temperature are the most significant parameters on warpage and wood content is the most significant on volumetric shrinkage. Packing pressure and wood content had no considerable effect on warpage and packing time on shrinkage too. To obtain optimal process conditions for minimum warpage and shrinkage, a multiobjective optimization based on Pareto front was developed. Response surface method was used to find the relationships between input parameters and objective functions, and genetic algorithm presented the Pareto front solutions to determine the optimum solution. It was observed that there was a good agreement between the predicted optimum values and the experiments.     

Warpage and Shrinkage Optimization of Injection-Molded Plastic Spoon Parts for Biodegradable Polymers Using Taguchi,ANOVA and Artificial Neural Network Methods

In this study, it is attempted to give an insight into the injection processability of three self-prepared polymers from A to Z. This work presents material analysis, injection molding simulation, design of experiments alongside considering all interaction effects of controlling parameters carefully for green biodegradable polymeric systems, including polylactic acid(PLA), polylactic acid-thermoplastic polyurethane(PLA-TPU) and polylactic acid-thermoplastic starch(PLA-TPS). The experiments were carried out using injection molding simulation software Autodesk Moldflow?in order to minimize warpage and volumetric shrinkage for each of the mentioned systems. The analysis was conducted by changing five significant processing parameters, including coolant temperature, packing time, packing pressure, mold temperature and melt temperature. Taguchi's L27(35) orthogonal array was selected as an efficient method for design of simulations in order to consider the interaction effects of the parameters and reduce spurious simulations. Meanwhile, artificial neural network(ANN) was also used for pattern recognition and optimization through modifying the processing conditions. The Taguchi coupled analysis of variance(ANOVA) and ANN analysis resulted in definition of optimum levels for each factor by two completely different methods. According to the results, melting temperature, coolant temperature and packing time had significant influence on the shrinkage and warpage. The ANN optimal level selection for minimization of shrinkage and/or warpage is in good agreement with ANOVA optimal level selection results. This investigation indicates that PLA-TPU compound exhibits the highest resistance to warpage and shrinkage defects compared to the other studied compounds.