模具技术进步带动注塑工艺发展

Affected by the global economic recession, Japanese injection molding machine manufacturer Nissei plastic Industrial Co., Ltd proposed for a substantial expansion of its plant capacity in China, which is opened in Japan＇s first production plant outside.     

Injection mold design of reverse engineering using injection molding analysis and machine learning

Plastic composites are used in vehicle components to improve fuel efficiency. Thus, the warpage of injection-molded plastic parts has become a quality issue. Factors, such as product shape and thickness, resin, and other injection molding conditions, can be modified to improve the warpage problem. However, if these factors are set with no possible adjustments, reverse engineering may be required. Reverse engineering is a difficult process that requires many trials and errors; thus, it is only used as a last resort. With respect to the warpage issue, reverse engineering considers the following: (1) Predicting and (2) modeling the warpage in opposite directions. Autodesk Moldflow Insight accommodates these key considerations, but many researchers are reluctant to use it. Although existing injectionmolding analysis programs are mainly used to predict qualitative results, computer-aided engineering (CAE) for reverse engineering requires quantitative analysis. Hence, the considerations are different from the existing analyses. An error in warpage prediction may lead to a costly mold modification because of the molds' complex structures. Quantitative warpage prediction for reverse engineering depends on process variables; thus, understanding how warpages are affected by uncertain process variables is important to improve the reliability of reverse engineering. Moreover, even if appropriate process variables are set, they cannot be applied due to tolerance in lengths. For this reason, mold shrinkage must be identified before designing a mold. This study conducted injection molding analysis for a radiator tank that uses glass fiber-reinforced plastic using Autodesk Moldflow Insight 2018.2. Data for warpage prediction were generated in accordance with five process variables to identify the relationship between the level of warpage and process variables. CAE also showed the level of mold shrinkage that can reduce warpage. In addition, a predictive model was created using the multilayer perceptron (MLP)- supervised learning technique, which is a deep learning method for artificial neural networks. The predictive model was compared with typical regression models, such as polynomial regression (also known as response surface model), EDT and RBF, to determine the optimal approximation model. The real modeling time for a radiator tank product is 1 h, but the MLP approximation model required only 1 min and 8 s to perform 8530 iterations with a similar reliability.

     

Effect of mold temperature on motion behavior of short glass fibers in injection molding process

In injection molding process, the mold temperature can strongly affect the fiber orientation and distribution state in plastic parts. The fiber orientation behavior is discussed, and a model is used to describe the layered structure in injection parts. By studying the injected specimens, the fiber distribution and the layered structure in the part are illustrated and a variation of the fiber distribution along with the increasing of the mold temperatures is also demonstrated. The surface morphologies of the fiber-reinforced specimens at different mold temperatures are analyzed which are used to study the effect of the mold temperature on the fiber motion process of the resultant parts. Results show that in proper mold temperature, the fibers can be completely covered in polymer matrix and the mold temperature can greatly affect the part surface quality.     

基于数值模拟的粉末注射成形模具结构优化设计

在粉注射成形过程中,模具结构的设计合理与否对成形质量和效率都有决定性影响.在基于数值模拟的基础上导出了粉末注射模具的浇注系统优化设计模型,并在MODEFLOW软件模拟和工艺实验中得到验证.结果表明优化后的模具在锁模力和成形周期方面都明显下降,生坯成形密度明显提高且密度方差明显减小,同时有效减少了试模次数,提高成形效率.     

Study of injection molding process simulation and mold design of automotive back door panel

Numerical simulation of the injection molding process of the outer panel of the automotive plastic rear door and mold design is presented here. Computer aided three-dimensional interactive application (CATIA) is employed to design the original automotive steel structure, and the modal and thermodynamic properties of the plastic back door outer panel are changed by changing the different injection materials of the back door outer panel. In order to efficiently design the panels, finite element analysis is used to verify whether the designed parts meet the mechanical properties requirements such as light weight, low fuel consumption, short production cycle, strong modeling design, high corrosion resistance and good recovery, the above main parameters have been evaluated, and the above main parameters are carried out evaluate. To simulate the injection molding process, computer aided engineering (CAE) software such as ANSYS and HyperWorks are used to analyze the back door of the selected material. After the numerical analysis, suitable material is selected, so that the modal and thermodynamic properties of the product could be satisfied as well as improved. Unigraphics NX (UG) is employed to design the convex and concave mold for the injection molding of the automobile’s plastic back door panel. Combined with the characteristics of the parts and the design requirements of the injection mold, the multi-scheme design of the pouring and cooling system is carried out. By comparing the effects of different gating and cooling systems on injection molding, the best gating and cooling system is selected. The artificial fish swarm algorithm is used to optimize the process parameters of the injection molding process, and the best combination of the injection molding process parameters of the outer panel of the rear door of the automobile is obtained.

     

Development of an in-process, gap-caused flash monitoring system in injection molding processes

This paper describes the development of an in-process, gap-caused flash monitoring (IGFM) system for injection-molding machines. An accelerometer sensor was integrated in the proposed IGFM system to detect the difference of the vibration signals between flash and non-flash products in the last period of the injection molding filling stage. Through an approach suggested by the statistical process control mechanism, the threshold in the decision-making mechanism of this system was established. That threshold then was used by the IGFM system to determine if flash occurred in the molded products when the machine was running. An experiment was designed and performed by manipulating the variables of gap and no-gap. The experimental testing results indicated that this system could successfully monitor injection-molded products’ flash status with approximately 94.7% accuracy while the machine was in process .     

基于Moldflow的薄板注塑件填充过程研究

本文对薄板注塑件的充填过程进行了充分的研究,对熔体前锋的充填模式、熔接线和气穴位置进行了的快速预测,并与实验结果进行了比较,理论计算模拟的结果与实验结果基本一致.     

Recalling of the growth of Bohai plastic injection molding market

The rapid development of many industries has brought great opportunities to rubber and plastic injection molding industry, although rubber and plastic injection molding market of Bohai Sea economic zone is smaller than Yangtze River Delta and Pearl River Delta economic zone.     

基于应变测量的注塑机调模机构调整方法

总结机械液压式注塑机调模机构失效的主要原因;提出基于拉杆应变测量的注塑机调模机构调整的方法;探讨注塑机设备管理的新思路.     

Surface microstructure replication in injection molding

In recent years, polymer components with surface microstructures have been in rising demand for applications such as lab-on-a-chip and optical components. Injection molding has proven to be a feasible and efficient way to manufacture such components. In injection molding, the mold surface topography is transcribed onto the plastic part through complex mechanisms. This replication, however, is not perfect, and the replication quality depends on the plastic material properties, the topography itself, and the process conditions. This paper describes and discusses an investigation of injection molding of surface microstructures. The fundamental problem of surface microstructure replication has been studied. The research is based on specific microstructures as found in lab-on-a-chip products and on rough surfaces generated from EDM (electro discharge machining) mold cavities. Emphasis is put on the ability to replicate surface microstructures under normal injection-molding conditions, i.e., with commodity materials within typical process windows. It was found that within typical process windows the replication quality depends significantly on several process parameters, and especially the mold temperature. For the specific microstructures, evidence suggests that step-height replication quality depends linearly on structure width in a certain range.     

Grey fuzzy PI control for packing pressure during injection molding process

This study presents a grey fuzzy PI (GFPI) controller for packing pressure control during the injection process. The novel controller was designed for solving the problems of large overshoot, static error, and long delay time on servo motor-driven injection molding machines. Based on reasonable assumptions, a mathematical model of injection system was established. According to the nonlinear, severe interferences, and long delay time characteristics in injection process, this paper integrates predictive grey system, robust fuzzy ratiocination, and PI control. Using these mathematical model and control algorithms, a GFPI controller is implemented into an MCU using C programming techniques. The integral discrete PID controller and solid fuzzy controller were realized for contrast experiments. The experimental results show that GFPI controller had better performance on reducing overshoot and static error, increasing both response rate and repeatable accuracy. Such a developed technology would provide helpful references for designing the controller of energy-saving servo motor-driven injection molding equipment.     

Automated surface finishing of plastic injection mold steel with spherical grinding and ball burnishing processes

This study investigates the possibilities of automated spherical grinding and ball burnishing surface finishing processes in a freeform surface plastic injection mold steel PDS5 on a CNC machining center. The design and manufacture of a grinding tool holder has been accomplished in this study. The optimal surface grinding parameters were determined using Taguchi’s orthogonal array method for plastic injection molding steel PDS5 on a machining center. The optimal surface grinding parameters for the plastic injection mold steel PDS5 were the combination of an abrasive material of PA Al₂O₃, a grinding speed of 18000 rpm, a grinding depth of 20 μm, and a feed of 50 mm/min. The surface roughness R_a of the specimen can be improved from about 1.60 μm to 0.35 μm by using the optimal parameters for surface grinding. Surface roughness R_a can be further improved from about 0.343 μm to 0.06 μm by using the ball burnishing process with the optimal burnishing parameters. Applying the optimal surface grinding and burnishing parameters sequentially to a fine-milled freeform surface mold insert, the surface roughness R_a of freeform surface region on the tested part can be improved from about 2.15 μm to 0.07 μm.     

An economic analysis comparing the cost feasibility of replacing injection molding processes with emerging additive manufacturing techniques

Additive manufacturing (AM) has proliferated in recent years and is displacing traditional manufacturing methods in numerous applications due to improvements in process efficiencies and cost reductions related to the evolving AM processes. This study explores the cost structure and break-even points of AM versus traditional methods. The comparative analysis examined the cost requirements of AM versus injection molding to manufacture various lot sizes of parts. Break-even points based on lot sizes and the relationship to the overall cost structure were also calculated. This research concludes that break-even points may be calculated based on part mass, density, and lot size.     

注塑工艺设计中模具CAE技术与正交试验的综合应用

模具CAE技术与正交实验、数据处理与分析技术的综合应用,可以有效地优化工艺参数方案,缩短模具设计周期、提高模具设计质量、降低模具制造成本。本文为注塑成型工艺方案的优化及模具设计提供了一种可行方案和技术路线。     

CAE技术在注塑模设计中的应用

利用Moldflow软件对汽车手柄内饰件的不同浇口位置进行流动模拟分析,预测可能存在的翘曲参数及锁模力的大小,确定最佳浇口位置。     

低压注塑机注射装置智能化温度控制研究

低压注塑机注射装置用于将塑化态的热熔胶注射至模腔内,其温度控制的稳定性和快速性关系到注塑制品质量。为研究该装置温度特性,提出了一种注射装置温控系统的近似模型,并采用自组织、自学习和自适应的径向基函数神经网络与PID控制相结合的控制策略。在该控制策略中,利用RBF神经网络提供的Jacobian矩阵信息实时调整PID控制参数。经仿真和测试证明该方法具有响应速度快、稳定性好的特点。     

粉末注射成形过程中熔体前沿速度优化

在粉末注射成形中,喂料熔体中的聚合物在充模阶段由于非均匀的熔体前沿速度将导致坯件非均匀收缩、坯件密度变小和翘曲变形.基于充填过程数值模拟提出实现在粉末注射成形过程中的注射速率优化方法,以获得均匀熔体前沿速度从而减少喂料中聚合物非均匀收缩以实现提高成形坯件密度.通过模拟熔体前沿面积变化曲线的与螺杆行程的关系,确定分级注射点;结合分级注射点对应的注射量与螺杆注射位置的对应关系,导出一个简化的分级注射参数.由模拟和实验表明,该方法能获得较为均匀的熔体前沿速度,熔体前沿速度的标准方差从优化前14.6 cm/s下降到优化后的42cm/s;生坯平均密度由从优化前5.34g/cm3提高到优化后的5.54g/cm3,生坯样本方差由从优化前0.235g/cm3下降到优化后的0.0823g/cm3.     

Flow patterns in gas-assisted injection molding process in a channel

The flow field of a long bubble steadily expelling a viscous fluid confined by two closely located parallel plates is examined. In order to investigate the influence of bubble size on the flow field, a theoretical bubble profile is used to replace the complicated procedure for computing simultaneously the interface between the gas surface and fluid flows. The present study showed the two typical flow patterns and also a third flow pattern of the stagnation point moving in the region of the bubble tip front during transformation of the two typical flow patterns. The vorticity patterns are also drawn for various bubble profiles and are examined for their effect on the flow. The velocity field is also presented from two different viewpoints and the phenomena is examined. The stagnation point located on the center line between the bubble tip to the upstream is only found in the small range of in a channel, where λ is ratio of the bubble width to the distance between two parallel plates.     

Simulations of gas penetration in thin plates designed with a semicircular gas channel during gas-assisted injection molding

Numerical simulations and experimental studies concerning gas and melt flows during gas-assisted injection molding of a thin plate designed with a gas channel of semicircular cross section were conducted. Distribution of the skin melt thickness along the gas penetration path was measured. Melt and gas flows in a gas channel of semicircular cross section were approximated by a model which uses a circular pipe of equivalent diameter superimposed on the thin plate. An algorithm based on the control-volume/finite-element method combined with a particle-tracing scheme using a dual-filling-parameter technique was utilized to predict both melt front and gas front advancements during the mold filling process. Simulated distribution of gas penetration shows reasonably good coincidence with the experimental observations.     

Improved state space model predictive fault-tolerant control for injection molding batch processes with partial actuator faults using GA optimization

A novel model predictive fault-tolerant control (MPFTC) strategy adopting genetic algorithm (GA) is proposed for batch processes under the case of disturbances and partial actuator faults. Based on the extended state space model in which the tracking error is contained, there are more degrees of freedom provided for the controller design and better control performance is obtained. In order to enhance the control performance further, the GA is introduced to optimize the relevant weighting matrices in the cost function. The effectiveness of the proposed MPFTC approach is tested on the injection velocity regulation of the injection molding process.