Multilayer injection molded transparent polymers are widely used in a variety of commercial and industrial applications, as key optical component. In multilayer injection molding, as the most typical feature of the process, the fusion interfaces and bonding behaviors between layers is a critical factor influencing the performance of the final product, while the characteristics has not been fully revealed in existing studies. Here, through theoretical and experimental perspectives, we thoroughly investigated the fusion interface characteristics of transparent polymers produced by multilayer injection molding. The fusion interface strength is used as the evaluation index of interface performance, and a theoretical strength model considering the characteristics of the multilayer injection molding process was established based on the molecular diffusion theory. Experimental studies on the fusion interface were conducted using a specially designed multilayer injection mold. Mechanical and microscopic characterizations show that increasing process temperatures, such as insert, melt, and mold temperatures, can significantly improve interface bonding strength. The proposed bonding strength theory can accurately predict experimental results, with the RMS error does not exceed 4 %. Moreover, the correlation between fusion interface properties and optical performance such as transmittance and haze were verified. Based on the above research, ultra-thick-walled optical products with a thickness of up to 30 mm were molded, achieving transmittance and haze values of 82.77 % and 0.05, respectively. The results reveal the properties of multilayer injection molding fusion interfaces of transparent polymers and will aid in the improvement of quality of thick-walled polymer optical products.

In conventional proportional–integral–derivative (PID) control, the integral term occupies a significant amount of controller memory, which prolongs the calculation time. The integral term easily leads to overshooting and oscillation, while the derivative term reduces the controller's anti-interference ability. In view of these problems, a PID expression with a recurrence relationship was derived, and the integral and differential terms of the conventional PID model were improved using an unsaturated integral and passivation differential to achieve a good control effect. Then, the improved PID was applied to the injection speed control of an injection molding machine, which is usually controlled using conventional PID control that featured difficulty in mathematical modeling, a nonlinear relationship between the input and the output, and high system complexity. Taking an injection molding machine as the control object, the transfer function of the injection system was constructed. Then, the improved PID was simulated using Matlab/Simulink. Lastly, the improved PID was verified using experiments. The simulation and the experimental results showed that the control model had a rapid response, no overshoot, and a high precision.

随着机器视觉技术的发展,在注塑成型行业得到广泛应用,有利于注塑智能制造技术的发展.首先介绍了机器视觉技术,综述了机器视觉技术在注塑成型加工中的两个主要应用模具监测和产品质量控制,最后对机器视觉技术在注塑成型加工中的应用进行了展望.

注射成形工艺参数是保障产品质量的关键因素.传统试错法严重依赖工艺人员的试模经验,随着注射成形工艺广泛应用于电子、航空航天等国家战略领域,产品的高端化对工艺参数智能化设置水平提出更高的要求.由于成形产品存在多方面的质量要求,且不同质量指标间可能相互制约,因此亟需一种工艺参数多目标智能优化方法,以获得不同优化目标间的帕累托最优.已有学者利用智能优化方法,如非支配排序遗传算法等,对多目标优化问题进行求解,但是此类方法需大量样本数据对质量-参数关系进行建模,存在试验次数多、且对不同材料及模具的适应性较差等问题.为解决上述问题,提出一种注射成形工艺参数多目标自学习优化方法,在优化过程中实时计算并更新各个工艺参数的梯度,并由不同质量指标的多梯度下降算法对多个目标函数进行优化,在优化过程中实现各工艺参数对产品质量影响程度的自主学习,省去了采集大量数据来建立多个质量模型的过程,实现了注射成形工艺参数的高效智能优化.在基准测试函数实验中,所提方法的优化结果与理论解的相对误差小于2％.同时数值仿真与注射成形实验结果表明,所提方法能高效获得多个优化目标的帕累托最优.

针对水平转盘对射机底座在自身重力作用下产生的结构变形大、对转盘底座静态性能的影响和运动惯性冲击大的问题,以轻量化和提高结构刚度、性能为目标,在对转盘底座进行静力学分析的基础上,利用拓扑优化方法对转盘底座进行结构设计.根据拓扑优化结果提出"转盘底座上下侧通孔优化""转盘底座四周出砂孔优化"及"转盘底座四周与上下侧通孔优化"3种结构设计方案.通过对这3种方案和原方案静、动态力学分析数据的对比,结果表明:"转盘底座四周出砂孔优化"可同时满足静力学及稳定性的要求,与原始方案相比,该方案质量减少了11.8％,最大等效应力降低了8.6％.

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.

The quality of the polymer raw material used in plastic processing methods is an important characteristic because it is one of the main factors in producing quality products. Therefore, the characterization of polymeric pellets in the polymer processing industry is very important to avoid using inferior materials. In general, differences in the interiors of polymeric pellets reflect differences in their densities. In this study, a high-sensitivity magnetic levitation method was used to characterize the polymeric pellets in four different occasions. The device used has a high sensitivity that can distinguish minute differences as small as of 0.0041 g/cm3 in density between different samples. In addition, the method can obtain a sample’s density without knowing the weight and volume of the sample. This method can be used to characterize materials by testing only a single pellet, which is very useful for polymeric pellet characterization.

Product weight is one of the most important properties for an injection-molded part. The determination of process parameters for obtaining an accurate weight is therefore essential. This study proposed a new optimization strategy for the injection-molding process in which the parameter optimization problem is converted to a weight classification problem. Injection-molded parts are produced under varying parameters and labeled as positive or negative compared with the standard weight, and the weight error of each sample is calculated. A support vector classifier (SVC) method is applied to construct a classification hyperplane in which the weight error is supposed to be zero. A particle swarm optimization (PSO) algorithm contributes to the tuning of the hyperparameters of the SVC model in order to minimize the error between the SVC prediction results and the experimental results. The proposed method is verified to be highly accurate, and its average weight error is 0.0212%. This method only requires a small amount of experiment samples and thus can reduce cost and time. This method has the potential to be widely promoted in the optimization of injection-molding process parameters.

Shrinkage voids have a large influence on the quality of plastic gears, and it is still a problem to detect the voids inside gears accurately and conveniently. This paper presents a novel method for detecting shrinkage voids via magnetic levitation. The porosity levels of plastic gears can be calculated using magnetic levitation because the density of plastic gears is influenced by the shrinkage voids. The distribution of shrinkage voids is quantified by the moment of volume, hence a theoretical model for the distributions of shrinkage voids and levitating posture can be established. Computer tomography (CT) detections were also carried out to verify the accuracy of magnetic levitation for detecting the shrinkage voids. Experimental results show that the average relative error of calculated porosity level is less than 7%, and the theoretical model for distribution of shrinkage voids agrees well with the results from CT detections, with the correlation coefficient being up to 99.8%. The proposed method has great potential for mass detection of plastic gears.

Nowadays, the plastic injection molding industry is ever-growing, crucial, and its plastic products can be seen everywhere. However, the mold damage problem still frustrates operators because of its high maintenance price and time-consuming maintenance process. This damage is commonly caused by foreign bodies in mold area, and the conventional mold protection method is insufficient for high-performance injection molding machines because of the uncertainty from many setting parameters. To improve detection precision of mold protection driven by a toggle mechanism (TM), this paper puts forward EMP, i.e., an extended Kalman filter (EKF) based self-adaptive mold protection method, wherein the EKF is used in current curve optimization, and the self-adaptive method (SAM) is proposed to gain an safety range of current curve. The EMP was verified in a 140-ton electric injection molding machine. Compared with a general method, the proposed method decreases the detected distance of mold protection by 22% under different thickness foreign bodies.

设计并制造在线测量注射成形过程中聚合物熔体黏度变化的装置.在测量装置中,非等温高剪切流变模具的型腔结构设计成厚度为1 mm或2 mm的狭缝,底部不封口,维持熔体的持续流动;在流动中心线上沿流动方向布置一组压力传感器实时检测聚合物熔体在模具型腔中的压力变化情况,并使用模温机控制模具温度.使用PXIe采集系统采集、显示、记录实验数据.实验通过压力传感器测量得到不同位置熔体压力,根据修正的牛顿黏性定律计算熔体黏度,并与Cross-WLF模型的理论值进行对比.实验结果表明:所设计的模具安全可靠,可获得低密度聚乙烯（LDPE）熔体在注射成形过程中熔体压力的变化情况,从而可以计算出材料在成形过程中的表观黏度演化情况.实验测量结果与理论值在剪切速率大于500 s-1的高剪切速度范围内较吻合,误差均在18%以内,最小为4%.该装置能满足真实成形条件下聚合物熔体信息的在线检测要求.

设计一种退芯模具,用以实现光学厚壁透镜的分层注塑,并使用Moldflow进行数值模拟分析;以三棱镜作为光学厚壁透镜制品代表,聚甲基丙烯酸甲酯(PMMA)为原材料,以光的相移角度为制品质量参照,模拟分析分层注射对注塑光学厚壁透镜制品光学质量的影响规律.结果表明,不同的分层工艺方式对注塑光学厚壁透镜的光学质量有着明显差异.通过模拟实验得到在该双层注射三棱镜模型中,层与层之间5 s的间隔、外层薄内层厚、先外后内包裹注射的分层方式最佳,层厚分布在各项工艺方式中对注塑效果影响最大,通过分层注射,可以减小光学厚壁透镜的平均体积收缩率.

由于二板式注射机合模机构涉及装配零件较多,实际工作时的受力状态难以简单计算.对合模机构的零部件进行适当简化,根据其工作原理,建立了有限元模型;通过有限元模拟分析发现,最大变形发生在定模板顶部,集中应力发生在拉杆与定模板孔连接处.该模拟分析结果,为进一步优化设计提供依据,也为合模机构的寿命预测的奠定基础.

Tie bars are the most important parts of injection molding machine, and the partial load of tie bars will directly affect the product quality. According to the measurement of strain and stress of the tie bars, the partial load rate of tie bars was calculated, and the influence of different types of thread shape and template (mold) parallelism on the partial load rate of tie bars were analyzed. Experiments reveal that the partial load rate is changed within 0.8%–3.8%, and the partial load rate gradually decreases with the increase of the clamping forces. Besides, different types of the thread of tie bars have little influence on the partial load rate, while the parallel degree of the template (mold) has great influence on the partial load rate of the tie bars. Further experiments show that the partial load rate is located in 0.79%–1.81% when the parallelism of template (mold) is good, and the partial load rate of tie bars between 8.59%–11.46% when the parallelism of template (mold) is poor. Finally, the partial load adjustment system of tie bars were also designed to make the force of tie bars more uniform and the partial load rate can be reduced by detecting the partial load rate of the tie bar and using the closed-loop control.

设计了一种新型四板注压式合模机构,该机构由肘杆机构完成第一次合模,由增压板完成第二次压缩成型,并对增压板及动模板进行有限元分析.结果表明,增压板及动模板的受力及变形在合模机构允许范围内,分布较均匀,能提高制品的成型精度.

提出挤注压一体化技术,采用新型肘杆直压复合式二次合模机构,利用二次压缩成型工艺解决了废弃塑料熔融料含气量大、流动性差等特性引起的注塑问题,提高了注塑制品的成型精度及质量;同时,利用连接装置完成“连续”挤出与“间歇”注塑压缩工作方式之间的协调与自动衔接,实现了固体废弃塑料到制品的直接转换.固体废弃塑料挤注压一体化设备的应用,在降低处理成本的同时极大地提高了固体废弃塑料回收再利用比例,实现了固体废弃塑料的高效处理与高值化再利用.

对负后角合模肘杆机构运动进行理论分析,并通过实际测量十字头的位移以及动模板的位移来实时分析合模机构的运动,包括合模机构的位移、速度以及加速度的关系.结果表明,注塑机的移模速度与油缸速度的速比与合模机构的参数有关,在合模过程的移模速度有明显的慢—快慢关系,实际测量与理论分析吻合度较好,具有良好的开闭模特性.

Motion analysis of negative-rear angle clamping toggle mechanism was carried out,and the stationary,rear,and moving plate structure were modeled and analyzed.The speed ratio of moving plate to clamping cylinder of the injection molding machine was related with the clamping mechanism parameters.There was no self-locking of negative-rear angle in the opening mold process,and the clamping process followed a slow-fast-slow mode.In the high-pressure clamping area,the speed of moving plate dropped very quickly.The structure of three plates was optimized through limited element analysis.