基于模腔压力的注塑过程注射速度设定曲线优化

注塑成型中,把熔前速度恒定(熔体均匀填充模具)作为设定注射速度参数的重要依据。针对熔前速度无法测量问题,提出对于一类注塑制品,用模腔压力随时间线性增加来近似熔前速度恒定。其次,利用实验数据,设计并建立了模腔压力递归神经网络(RNN)模型。在此基础上,提出一种注射速度设定曲线的分级优化策略,其中曲线分级是利用Douglas-Peucker方法自动确定速度分级数目和位置,优化过程则采取基于滑动窗口的迭代优化方法来实现。实验结果表明,该优化方法可以根据模腔复杂程度自动选择合适的注射曲线分级数目,并且其优化精度较常规等间隔分级优化方法更高。     

注塑机注射速度的模型预测控制及其仿真

注塑过程具有随机性、非线性以及时变性等特点,常规比例积分微分控制方法很难使注射速度控制达到理想的效果,为此提出了一种基于模型预测的注射速度控制方法。首先介绍了注塑机注塑工作原理,分析了注射速度控制系统,并通过模型预测算法得到当前采样时刻控制量以及下一时刻的控制量。仿真结果表明,基于模型预测的注射速度控制能够很好地跟踪快速变化的速度设定曲线,拥有较好的稳定性和抗干扰性。     

A study of rib geometry for gas-assisted injection molding

Large, thin, plate-shaped parts usually are strengthened with structural ribs. Ribs also serve as gas channels with gas-assisted technology. The layout and geometry of these gas-channel ribs are critical to the gas-assisted injection molding (GAIM) process. In this study, the effects of rib geometry, including aspect ratio and fillet geometry, on the GAIM process are investigated. Experimental results indicate that increasing the rib width widens the allowable operation range and thus improves the moldability. Adding fillets to the rib corner significantly enhances the moldability. Adding fillets also reduces the loss of rigidity due to void formation in the rib. A curved fillet improves moldability and rigidity more than one that is straight.     

Optimal anticipatory control of ram velocity in injection molding

This paper discusses a computer control system for ram velocity of an injection molding machine using optimal state feedback based on the linear quadratic control theory. A new approach for the selection of appropriate weighting matrices is presented in this context. The simulation results reveal that the optimal controller has improved performance over the conventional PID controller presently used, having faster speed of response, significantly better tracking performance, and better noise filtering properties. The execution speed and the core storage requirements would allow implementation even on a small online computer.     

Deformation velocity dependence on tensile fracture characteristics of polypropylene injection molding parts

To clarify the mechanism of the deformation and fracture in a low‐velocity impact test on the isotactic polypropylene (i‐PP) sheet made by injection molding, the change of the style of fracture and the form of deformation was examined while changing the speed of the striker in a low‐velocity impact test. In the injection molding sheet, an oriented skin layer of some thickness is formed on the surface of the sample sheet. By the stress perpendicular to the orientation direction of the skin layer, crazes were formed easily in parallel with the orientation direction in this layer, and cracks were formed from there. Because these cracks bring the sample sheet a strong restraint of strain, a high stress concentration occurs at the end of this crack even if the formation of the oriented layer is limited on the surface of the sample sheet only, and the low‐velocity impact test leads the sample sheet to a brittle fracture. As a result, the injection molding sheet that forms oriented structure on its surface causes the ductility‐brittleness transform at a lower velocity of deformation compared with the nonoriented sheet. POLYM. ENG. SCI., 53:2659–2665, 2013. © 2013 Society of Plastics Engineers     

Numerical simulation of reactive injection molding in a radial flow geometry

The radial flow of a chemically reactive fluid between two parallel circular disks during the process of Reactive Injection Molding (RIM) has been simulated in a decelerative, non-isothermal, transient flow environment. The effects of key operating and system parameters (feed temperature, volumetric flow rate, reaction rate, and cavity thickness) on velocity, conversion, and temperature profiles which occur in this decelerative flow environment were determined. A catalyzed, unfilled polyurethane RIM system was modeled by a linear step polymerization scheme using average literature values for the reaction rate, and thermodynamic and constitutive parameters. The numerical solution was achieved using the method of lines and upwind approximations of the spatial derivatives. The geometry studied (two parallel, center gated circular disks) models flow patterns in commercial RIM processes more realistically than the rectangular flow between two parallel surfaces (studied by previous workers) in which the average velocity is constant along the length of the mold. This simulation predicts the accumulation of high polymer near the entrance to the mold and near the outer edge of the cavity in fast reactive systems. The accumulation of material near the gate results in viscous heat generation and a maximum in temperature in the region immediately downstream from the restriction.     

Automatic velocity profile determination for uniform filling in injection molding

The filling phase plays an important role in determining the quality of injection molded parts. Uniform melt‐front velocity has been recommended for minimizing the part non‐uniformity. On the basis of a capacitive transducer that has been developed for online measurement of melt front velocity, we propose an intelligent strategy for profiling injection velocity. The nonlinear response of melt development in a mold cavity is first acquired with a constant screw injection velocity. On the basis of this response, a stage division method is proposed to determine an appropriate stage number of a piecewise linear profile and the locations of the switch points. An optimization based on sequential simplex search is then conducted to search for the optimal profile of injection velocity. Online experimental tests on molds with different geometries show that the proposed method is effective in achieving a uniform mold filling. POLYM. ENG. SCI., 2010. © 2010 Society of Plastics Engineers     

Control of injection velocity using a fuzzy logic rule-based controller for thermoplastics injection molding

Injection velocity to a large degree determines the melt injection rate during the injection phase, and it has critical impact on the molded part quality, such as shrinkage, warpage, and impact strength. An injection molding machine operates with different injection velocity profiles, barrel temperatures, molds, and materials. These strongly different molding conditions cause the injection velocity dynamics to very significantly and to make the control performance of the injection velocity poor with a typical PID controller. A real-time, closed-loop feedback and feedforward control system based on fuzzy logic has been designed, developed, and implemented to control the injection velocity. The fuzzy logic rules of the controller are optimized by analyzing phase plane characteristics. The controller output membership functions are optimized based on a 2^k factorial design technique. The experimental results reveal that the fuzzy logic-based controller works well with different molds, materials, barrel temperatures, and injection velocity profiles, indicating that the fuzzy logic controller has superior performance over the conventional PID controller in response speed, set-point tracking ability, noise rejection, and robustness.     

Observers for optimal anticipatory control of ram velocity in injection molding

The application of optimal anticipatory control assumes that the entire stare is available for feedback. However, in the case of injection molding this assumption is viola red due to economic considerations. For that purpose, this paper discusses the effectiveness of optimal anticipatory control using estimates of the states obtained from a dynamic system, called observer. State estimation is essential to optimal control techniques since in general the states are used in some form of feedback and the number of measurable states is usually much Jess than the actual number of state variables, limited by the availability of cheap and rugged sensors and the ease of installation. Furthermore the measurements from the existing sensors may be corrupted by significant noise. In the present paper both the stochastic and the deterministic cases are investigated for application to optimal control of ram velocity in injection molding.     

基于优劣解距离法⁃灰色关联分析的注射成型质量多目标优化

为提高座厕椅面板注射成型质量,将优劣解距离法（TOPSIS）与灰色关联分析相结合,提出了基于TOPSIS的灰色关联综合评价模型。首先,优化并确定了塑件浇注系统,然后进行正交试验设计,选择模具温度、熔体温度,注射时间、保压压力、保压时间为试验因素,以翘曲变形量、缩痕指数、体积收缩率为评价指标,运用Moldflow软件进行模拟分析;根据正交试验数据,利用基于指标相关性的指标权重确定（CRITIC）法确定了各评价指标权重系数,采用基于TOPSIS的灰色关联综合评价方法,将多目标优化转化为单目标优化问题,获得了塑件的最佳注塑工艺参数组合。结果表明,优化后的塑件体积收缩率降低14.6 %、缩痕指数降低43.3 %,翘曲变形量与优化前基本一致,塑件综合质量显著提高。     

注塑成型工艺对透明PP光学性能的影响

采用不同的工艺条件注塑成型无规共聚透明聚丙烯(PP),测试透光率、雾度和表面光泽度,分析了成型工艺参数对制品光学性能的影响。所选透明PP的最佳注塑工艺为:加工温度220～230℃,模具温度40～60℃。在保证制品顺利成型的情况下应尽量采用较小的注塑压力。注塑速率和注塑时间对制品的光学性能影响较小。     

Pattern-based closed-loop quality control for the injection molding process

The basis for a novel pattern-based closed-loop control strategy for the injection molding process is presented. The strategy uses artificial neural networks (ANNs) embedded within a cascade design to analyze sensor patterns, identify process character and control part quality. The platform for this work, the injection molding process, is an industrially significant, cyclic manufacturing operation. Final part quality of this process is a nonlinear function of many machine and polymer variables. Part quality control of this process is currently attained via single input–single output machine controls supervised by human operators. Presented here is a method that employs ANN technology to improve upon this approach and provide the basis for closed-loop part quality control. In the cascade design, machine controller set-points of an inner loop are updated based on ANN analysis of mold cavity pressure patterns. The controller action maintains the desired pressure pattern set-point of the outer loop associated with desired part quality. Control strategy details are provided along with set-point tracking demonstrations that support feasibility of this pattern-based approach.     

橡胶注射成型机注射装置结构分析研究

主要介绍了橡胶注射成型机及其注射装置的发展情况,阐述了橡胶注射成型的特点以及注射装置设计要求,并对三种常用的注射装置的结构特点及应用作系统的分析比较.     

Online pattern-based part quality monitoring of the injection molding process

The quality of injection molded parts is currently monitored in the plant using techniques that focus on the statistical analysis of discrete data and, in particular, peak values. This paper presents an alternative online technique for part quality monitoring that focuses on the analysis of complete data patterns. Specifically, this paper discusses the application of artificial neural networks (ANNs) as part quality monitoring tools. The method of approach is to train a back propagation network (BPN) to associate part quality with the corresponding data pattern produced during injection. In Part I of this work, the data pattern consists of a series of discrete values and the part quality measure is defined as part weight. In Part II, the data pattern is the measurement profile observed from a pressure sensor placed in the mold cavity and the part quality measure is defined as part length. Results show that ANNs are successful in predicting part quality based on data patterns when an entire sensor profile is analyzed. Furthermore, demonstrations show that the approach is superior in predicting part quality when compared to statistical techniques now widely practiced by the injection molding process industry.     

Visualization of particles arrangement during filling stage of polyamide 6 – metal insert injection molding

An isotactic polypropylene filled with talc and mica particles was used for visualization of molten polymer flow lines during filling of mold cavity with metal insert. The talc particles orientation in polypropylene matrix was followed by scanning electron microscopy. For the quantification of platelet particles orientation in molten polymer flow localized near metal wall, the Herman's function was applied. An existence of regions with well oriented, randomly organized talc particles depending on the shape and cross‐section of the channels, was found and reported. The domain with the most disorganized platelet particles was detected in the region where polymer streamed around the sharp corner of the metal insert. Such a kind of disarranged region could be the weakest part of the whole injection molded polymeric element. POLYM. ENG. SCI., 59:E271–E278, 2019. © 2019 Society of Plastics Engineers     

Compression molding of sheet molding compounds in plate-rib type geometry

The flow of fiber-reinforced composite materials in a plate-rib type mold geometry during compression molding was investigated using a series of sheet molding compounds (SMC). Material anisotropy in relation to the amount and the length of reinforcing fibers was analyzed. The influence of the interfacial friction between SMC charge and the mold surface on the flow and sink mark formation was also examined. The results were explained qualitatively by computer simulation.     

Coupled analysis of injection molding filling and fiber orientation,including in-plane velocity gradient effect

On injection molding of short fiber reinforced plastics, fiber orientation during mold filling is determined by the flow field and the interactions between the fibers. The flow field is, in turn, affected by the orientation of fibers. The Dinh and Armstrong rheological equation of state for semiconcentrated fiber suspensions was incorporated into the coupled analysis of mold filling flow and fiber orientation. The viscous shear stress and extra shear stress due to fibers dominate the momentum balance in the coupled Hele-Shaw flow approximation, but the extra in-plane stretching stress terms could be of the same order as those shear stress terms, for large in-plane stretching of suspensions of large particle number. Therefore, a new pressure equation, governing the mold filling process, was derived, including the stresses due to the in-plane velocity gradients. The mold filling simulation was then performed by solving the new pressure equation and the energy equation via a finite element/finite difference method, as well as evolution equations for the second-order orientation tensor via the fourth-order Runge-Kutta method. The effects of stresses due to the in-plane velocity gradient on pressure, velocity, and fiber orientation fields were investigated in the center-gated radial diverging flow in the cases of both an isothermal Newtonian fluid matrix and a nonisothermal polymeric matrix. In particular, the in-plane velocity gradient effect on the fiber orientation was found to be significant near the gate, and more notably for the case of a nonisothermal polymer matrix.     

基于工况识别的注塑过程产品质量预测方法

针对多工况注塑过程的在线质量预测问题,考虑了过程数据高维、耦合、非线性等特点,采用拉普拉斯特征映射(LE)方法实现过程数据的非线性降维;在低维特征空间中采用Mean Shift聚类算法完成样本的工况聚类,以便注塑过程的工况分析和知识挖掘;同时运用Mean Shift原理,提出一种新样本的在线工况识别方法;最后应用基于混合粒子群(PSO)参数寻优的偏最小二乘支持向量机(PLS-LSSVM)方法,建立了多工况注塑过程的产品质量软测量模型。实验结果表明,相较于PLS-LSSVM方法,本文方法的预测精度和泛化性能均有明显提高,可为实际注塑企业提供一种效果良好的多工况产品质量在线预测方法。     

An investigation on the application of predictive control for controlling screw position and velocity on an injection molding machine

Injection velocity is one of the key parameters in the injection molding process that has significant effect on part quality, influencing common problems, such as flashing and short shots. Different products require specific molding conditions, including mold and melt temperatures, velocity profiles, and polymers, making the injection velocity dynamics vary significantly and difficult for high precision velocity control. Two predictive controllers were developed to control the screw injection velocity. The first approach uses a position sensor as feedback and a simplified predictive controller to track an injection velocity setpoint profile. The controller was developed and implemented utilizing single‐step change and multistep change open loop tests. The second strategy uses a multimodel dynamic matrix predictive controller to overcome the nonlinear characteristics of the injection velocity dynamics as the mold is being filled. Velocity feedback is provided by high speed processing of the position analog signal. This approach utilizes several open loop injection velocity profiles to generate corresponding dynamic matrices for the controller. As a result, this controller is modified or retuned automatically when setpoint changes in injection velocity occur, as well as when using different polymers and molds. The close loop results for both simulations and real time control have demonstrated that the two predictive controllers provided good setpoint tracking performance for wide ranging position and velocity profiles. POLYM. ENG. SCI., 47:390–399, 2007. © 2007 Society of Plastics Engineers.     

A physical model for a quality control concept in injection molding

In this work, a model is presented, which is the basis of a quality control concept for the injection molding process. Contrary to statistical methods, this model uses physical dependencies of two quality parameters on four influencing parameters. The influences of holding pressure, holding time, melt temperature, and mold temperature on part mass and dimensions are described based on the fundamental material behavior such as pvT‐data or energy equation. Furthermore, the influence of viscosity changes is indirectly taken into account using the injection work. Assuming only small deviations of the influencing parameters around an optimized operating point, the four parameters are treated as being independent from each other. With this assumption, a product ansatz was chosen with different functions for each influencing factor. Applying basic algebra, the starting equation was transformed into a form that describes either the change in part mass or characteristic part dimensions as a function of the influencing factors. The final equation for the part mass contains six model parameters, whereas nine model parameters are necessary for the equation for the part length. To obtain those model parameters some systematic experiments are required. Once the parameters are known, the model is able to calculate the change of the target values when the influencing factors vary around the operating point. The model was tested experimentally with focus on dimensions using a plastic cover made of an acrylonitrile butadiene styrene (ABS) grade. For the investigated part geometry and material grade, the process behavior was described well by the model. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011