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.     

基于BP-NSGA的注塑参数多目标智能优化设计

为获得成型性能最优的注塑参数设计方案,提出了基于BP神经网络和非支配排序遗传算法的注塑参数多目标优化方法。将注塑模结构尺寸参数和注塑工艺参数作为待优化的设计变量,建立了以高质量、低成本、高效率为优化目标的注塑参数优化设计模型。基于非支配排序遗传算法获取给定参数范围内的所有Pareto最优解,并通过建立多输入和多输出的BP神经网络来快速获得非支配排序遗传算法优化进程中所有个体的适应度值。开发了基于BP神经网络与非支配排序遗传算法集成的注塑参数智能优化设计系统,并通过鼠标注塑参数设计实例,验证了其适用性和有效性。     

Minimizing manufacturing costs for thin injection molded plastic components

Minimizing the cost of manufacturing a plastic component is very important in the highly competitive plastic injection molding industry. The current approach of R&D work focuses on optimizing the dimensions of the plastic component, particularly in reducing the thickness of the component during product design, the first phase of manufacturing, in order to minimize the manufacturing cost. This approach treats the component dimensions established in the product design phase as the given input, and uses optimization techniques to reduce the manufacturing cost of mold design and molding for producing the component. In most cases, the current approach provides the correct solution for minimizing the manufacturing cost. However, when the approach is applied to a thin component, typically when miniaturizing products, it has problems finding the true minimum manufacturing cost. This paper analyses the shortcomings of the current approach for handling thin plastic components and proposes a method to overcome them. A worked example is used to illustrate the problems and compare the differences when using the current approach and the new method proposed in the paper.     

Minimizing manufacturing costs for thin injection molded plastic components

Minimizing the cost of manufacturing a plastic component is very important in the highly competitive plastic injection molding industry. The current approach of R&D work focuses on optimizing the dimensions of the plastic component, particularly in reducing the thickness of the component during product design, the first phase of manufacturing, in order to minimize the manufacturing cost. This approach treats the component dimensions established in the product design phase as the given input, and uses optimization techniques to reduce the manufacturing cost of mold design and molding for producing the component. In most cases, the current approach provides the correct solution for minimizing the manufacturing cost. However, when the approach is applied to a thin component, typically when miniaturizing products, it has problems finding the true minimum manufacturing cost. This paper analyses the shortcomings of the current approach for handling thin plastic components and proposes a method to overcome them. A worked example is used to illustrate the problems and compare the differences when using the current approach and the new method proposed in the paper.     

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。     

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.     

Optimal injection molding conditions considering the core shift for a plastic battery case with thin and deep walls

The objective of this paper is to examine the influence of injection molding parameters on the core shift to obtain the optimal injection molding conditions of a plastic battery case with thin and deep walls using numerical analyses and experiments. Unlike conventional injection molding analysis, the flexible parts of the mold were represented by 3-D tetrahedron meshes to consider the core shift in the numerical analysis. The design of experiments (DOE) was used to estimate the proper molding conditions that minimize the core shift and a dominant parameter. The results of the DOE showed that the dominant parameter is the injection pressure, and the core shift decreases when the injection pressure decreases. In addition, it was shown that the initial mold temperature and the injection time hardly affect the core shift. The results of the experiments showed that products without warpage are manufactured when the injection pressure is nearly 32 MPa. Comparing the results of the analyses with those of the experiments, optimal injection molding conditions were determined. In addition, it was shown that the core shift should be considered to simulate the injection molding process of a plastic battery case with thin and deep walls.     

Optimal design of medium channels for water-assisted rapid thermal cycle mold using multi-objective evolutionary algorithm and multi-attribute decision-making method

Rapid heat cycle molding technology developed recently is a novel polymer injection molding process. In this study, a new water-assisted rapid heat cycle molding (WRHCM) mold used for producing a large-size air-conditioning plastic panel was investigated. Aiming at improving heating efficiency and temperature distribution uniformity of the mold cavity surface, a two-stage optimization approach was proposed to determine the optimal design parameters of medium channels for the WRHCM mold. First of all, the non-dominated sorting genetic algorithm-II (NSGA-II) combined with surrogate models was employed to search the Pareto-optimal solutions. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution was adopted as a multi-attribute decision-making method to determine the best compromise solution from the Pareto set. Then, the layout of the medium channels for this air-conditioning panel WRHCM mold was optimized based on the developed optimization method. It was indicated that the heating efficiency and temperature distribution uniformity on the mold cavity surface were greatly improved by using the optimal design results. Furthermore, the effectiveness of the optimization method proposed in this study was validated by an industrial application.     

Experimental-based optimization of polymer injection molding process parameters using anfis-ga method

Compared with ordinary injection-molded parts, the slender, cantilevered, and thin-walled plastic parts are harsh on the injection molding process conditions. For complexity and particularity, it is difficult to form such parts. It is also more likely to cause excessive warpage deformation, affecting the molding quality and performance. The automobile audio shell is a typical slender, cantilevered, thin-walled plastic part. When the mold structure and material are determined, optimizing its injection molding process is the most economical and effective method to manufacture the products with the optimum properties. In order to minimize the warpage deformation, the adaptive network based fuzzy inference system (ANFIS) and genetic algorithm (GA) were adopted to optimize the injection molding process parameters. In particular, considering the high-dimensional nonlinear relationship between the process parameters and the warpage, the ANFIS is constructed as the prediction model of the warpage. Then, the GA is used to globally optimize the prediction model to determine the optimal process parameters. The results show that the optimization method based on ANFIS-GA has a good performance. The warpage is reduced to 0.0925 mm while reduced by 88.25 %. The optimal injection molding process parameters are used for simulation and manufacture, verifying the effectiveness and reliability of the optimization method.

     

Integrated simulation of the injection molding process with stereolithography molds

Functional parts are needed for design verification testing, field trials, customer evaluation, and production planning. By eliminating multiple steps, the creation of the injection mold directly by a rapid prototyping (RP) process holds the best promise of reducing the time and cost needed to mold low-volume quantities of parts. The potential of this integration of injection molding with RP has been demonstrated many times. What is missing is the fundamental understanding of how the modifications to the mold material and RP manufacturing process impact both the mold design and the injection molding process. In addition, numerical simulation techniques have now become helpful tools of mold designers and process engineers for traditional injection molding. But all current simulation packages for conventional injection molding are no longer applicable to this new type of injection molds, mainly because the property of the mold material changes greatly. In this paper, an integrated approach to accomplish a numerical simulation of injection molding into rapid-prototyped molds is established and a corresponding simulation system is developed. Comparisons with experimental results are employed for verification, which show that the present scheme is well suited to handle RP fabricated stereolithography (SL) molds.     

[成形过程的数据挖掘与深度学习方法]塑料注射成形智能技术及其应用

总结了当前塑料注射成形的产业需求和技术瓶颈，阐明了未来的发展趋势。根据塑料注射成形特性，提出“注射成形智能制造体系”的科学框架，建立以传感技术、工业以太网及互联网为基础的智能注射成形解决方案。围绕智能设计、智能优化、智能监控及制造数据平台四个层面，总结了注射成形中知识的组织与重用、自主决策与优化、过程感知与检测及云服务等技术，为实现塑料注射成形与新一代人工智能技术的深度融合指出了重要发展方向。     

Process parameters optimization of injection molding using a fast strip analysis as a surrogate model

Injection molding process parameters such as injection temperature, mold temperature, and injection time have direct influence on the quality and cost of products. However, the optimization of these parameters is a complex and difficult task. In this paper, a novel surrogate-based evolutionary algorithm for process parameters optimization is proposed. Considering that most injection molded parts have a sheet like geometry, a fast strip analysis model is adopted as a surrogate model to approximate the time-consuming computer simulation software for predicating the filling characteristics of injection molding, in which the original part is represented by a rectangular strip, and a finite difference method is adopted to solve one dimensional flow in the strip. Having established the surrogate model, a particle swarm optimization algorithm is employed to find out the optimum process parameters over a space of all feasible process parameters. Case studies show that the proposed optimization algorithm can optimize the process parameters effectively.     

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.     

Optimization of conformal cooling channels with array of baffles for plastic injection mold

Cooling system has an important role in the injection molding process in terms of not only productivity and quality, but also mold-making cost. In this paper, a conformal cooling channel with an array of baffles is proposed for obtaining uniform cooling over the entire free-form surface of molded parts. A new algorithm for calculating temperature distribution through molding thickness, mold surface temperature and cooling time was presented. The relation among cooling channels’ configuration, process parameters, mold material, molding thickness and temperature distribution in the mold for a given polymer is expressed by a system of approximate equations. This relation was established by the design of experiment and response surface methodology based on an adequate physical-mathematical model, finite difference method and numerical simulation. By applying this approximate mathematical relation, the optimization process for obtaining target mold temperature, uniform temperature distribution and minimizing the cooling time becomes more effective. Two case studies were carried out to test and validate the proposed method. The results show that present approach improves the cooling performance and facilitates the mold design process in comparison to the trial-and-error simulation-based method.     

Study on temperature field for invar alloy during TIG welding

In order to solve the complex multi-objective optimal performance design of large-scale injection molding machines, NSGA-II is used to find a much better spread of design solutions and better convergence near the true Pareto-optimal front. The combination of the design method and the injection molding machine is discussed. Screw diameter performance, stick inside distance performance, mold moving route performance and mold-locked force performance are chosen as the four main performance evaluation indexes. Some related parameters are associated to get a performance indication. And performance optimization design parameter constraints are listed to make the design solutions to have practical significance. The mathematical models of two objectives and the mathematical models of three objectives are analyzed. Finally, the instance of HTF180X1N large-scale injection molding machine is taken as an example to demonstrated that such method is effective and practical.     

低压注塑设备拉杆式合模机构的分析与优化

低压注塑设备在使用过程中,容易产生拉杆式合模机构抬模及压合板变形等问题,导致注塑后产品质量异常。针对以上问题,应用SolidWorks软件对拉杆式合模机构进行建模,通过ANSYS Workbench软件进行静力学最大应力和总变形数值分析,以及拓扑优化。经拓扑优化后,活动压合模板的质量减小了11.3%,局部最大应力由342 MPa减小为291 MPa,最大变形量由0.133 mm减小为0.089 mm。通过对拉杆式合模机构进行分析和优化,提高了其静力学性能,满足低压注塑设备生产中的压合注塑要求,同时提高了设备运行的稳定性。     

Characteristics analysis of cellular bucket brigades with different constraints

Reconfigurable machines are used in various manufacturing processes increasingly, so that the system could be adapted to successive market changes, changes in customer requirements, and competition among manufacturers. This makes necessary designing reconfigurable machines that can get into the market as soon as possible. Injection molding machines are an example of an equipment that requires reconfigurability, and the mold is one of the machine modules requiring further attention. This article provides a design methodology that helps designers to decide which mold configuration is appropriate to produce a molded part family. Proposed methodology brings together classical methodologies and design modern tools, and establishes a sequence of activities during the product architecture. This adjustment provides a useful tool in the conceptual definition of the mold architecture and facilitates the preliminary design of molds. Decisions are based on nature and predominant features of conventional products which are manufactured by injection molding. A characterization of common products obtained by molding is proposed as a support database for developing the methodology. In addition, in this work, a case study is developed in order to illustrate how the methodology can be performed. Benefits and advantages of the model are summarized as well.     

基于MPI的注塑成型分析

介绍了注塑CAE软件-MPI(Moldflow Plastics Insight)的应用流程和方法,应用MPI软件进行制件注塑成型过程模拟分析,优化模具浇注系统、冷却系统和注射成型工艺方案,为生产优质塑料制件提供理论指导.     

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。