General frameworks for optimization of plastic injection molding process parameters

Plastic injection molding is widely used for manufacturing a variety of parts. Molding conditions or process parameters play a decisive role that affects the quality and productivity of plastic products. This work reviews the state-of-the-art of the process parameter optimization for plastic injection molding. The characteristics, advantages, disadvantages, and scope of application of all of the common optimization approaches such as response surface model, Kriging model, artificial neural network, genetic algorithms, and hybrid approaches are addressed. In addition, two general frameworks for simulation-based optimization of injection molding process parameter, including direct optimization and metamodeling optimization, are proposed as recommended paradigms. Two case studies are illustrated in order to demonstrate the implementation of the suggested frameworks and to compare among these optimization methods. This work is intended as a contribution to facilitate the optimization of plastic injection molding process parameter.     

Numerical and experimental investigation of process parameters optimization in plastic injection molding using multi-criteria decision making

In plastic injection molding (PIM), the process parameters such as packing pressure, melt temperature, and cooling time should be adjusted and optimized for high product quality and high productivity. Warpage is one of the major defects in the PIM and should be minimized for high quality. Cycle time should be minimized for the high productivity. In addition to the warpage and the cycle time, clamping force affects the product both the quality and the productivity. Therefore, for the high product quality and the high productivity, it is important to minimize the warpage, the cycle time and the clamping force simultaneously. In this paper, a multi-objective optimization of process parameters in PIM for minimizing three objectives is performed. Numerical simulation in the PIM is generally so intensive that a sequential approximate optimization using radial basis function network is adopted to determine the optimal process parameters. The radar chart is used to perform the trade-off analysis among three objective functions. In addition, the better and worse solution are newly introduced for the trade-off analysis. It is found through the trade-off analysis that all objective functions of the conformal cooling channel are well improved in comparison with the ones of the conventional cooling channel. Therefore, 43% warpage reduction, 1,7% clamping force reduction, and 47% cycle time reduction can successfully be achieved using the conformal cooling channel. Based on the numerical result, the experiment using PIM machine (GL30-LP, Sodick) is carried out. The conformal cooling channel is developed by the metal 3D printer (OPM250L, Sodick). Through the numerical and experimental result, the validity of the proposed approach is examined.     

Expert systems in engineering design: an application for injection molding of plastic parts

The rich development environments of expert system shells provide tools for developing knowledge-based expert systems for complex tasks such as engineering design. The diverse knowledge in engineering design combines heuristics with deterministic knowledge, from multiple sources, and involves complicated, interrelated components. The hybrid capabilities in emerging expert system tools effectively address this diverse knowledge, and facilitate the rapid development of design aids by the engineering designer. A prototype expert system for injection-molded plastic parts demonstrates the utility of expert systems for design applications. The prototype is implemented in an object-oriented, rule-based environment, and incorporates solid modeling software and external material databases.     

Intelligent setting of process parameters for injection molding based on case-based reasoning of molding features

Journal of Intelligent Manufacturing - Process parameters of injection molding are the key factors affecting the final quality and the molding efficiency of products. In the traditional automatic...     

Cost estimation of plastic injection molding parts through integration of PSO and BP neural network

Plastic injection molding technology has been widely used in a variety of high-tech products, auto parts and generic household products. Against the waves of globalization, the plastic injection enterprises must shorten time-to-market to enhancement of competence, and launch products ahead of all other competitors, and thus they can quickly seize a big target market and lead the price. The backpropagation (BP) neural network was used in this study to construct an estimating model for the cost of plastic injection molding parts so as to reduce the complexity in the traditional cost estimating procedures. Because the parameters of BP neural network have a significant influence on results, and particle swarm optimization (PSO) is capable of quickly finding optimal solutions. We integrated PSO and BP neural network so that the convergence rate was improved and precision was relatively enhanced through particle evolutions based on the optimum parameter combination from BP neural network.     

A neural network-based approach for dynamic quality prediction in a plastic injection molding process

This paper presents an innovative neural network-based quality prediction system for a plastic injection molding process. A self-organizing map plus a back-propagation neural network (SOM-BPNN) model is proposed for creating a dynamic quality predictor. Three SOM-based dynamic extraction parameters with six manufacturing process parameters and one level of product quality were dedicated to training and testing the proposed system. In addition, Taguchi’s parameter design method was also applied to enhance the neural network performance. For comparison, an additional back-propagation neural network (BPNN) model was constructed for which six process parameters were used for training and testing. The training and testing data for the two models respectively consisted of 120 and 40 samples. Experimental results showed that such a SOM-BPNN-based model can accurately predict the product quality (weight) and can likely be used for various practical applications.     

Numerical simulation and experimental analysis of the sintered micro-parts using the powder injection molding process

Microsystem Technologies - This paper discusses in detail the development of numerical simulations capable of simulating structural evolution and macroscopic deformation during a powder injection...     

Spiral and conformal cooling in plastic injection molding

Designing cooling channels for the thermoplastic injection process is a very important step in mold design. A conformal cooling channel can significantly improve the efficiency and the quality of production in plastic injection molding. This paper introduces an approach to generate spiral channels for conformal cooling. The cooling channels designed by our algorithms has very simple connectivity and can achieve effective conformal cooling for the models with complex shapes. The axial curves of cooling channels are constructed on a free-form surface conformal to the mold surface. With the help of boundary-distance maps, algorithms are investigated to generate evenly distributed spiral curves on the surface. The cooling channels derived from these spiral curves are conformal to the plastic part and introduce nearly no reduction at the rate of coolant flow. Therefore, the channels are able to achieve uniform mold cooling. Moreover, by having simple connectivity, these spiral channels can be fabricated by copper duct bending instead of expensive selective laser sintering.     

Multi-objective optimization of volume shrinkage and clamping force for plastic injection molding via sequential approximate optimization

Process parameters in plastic injection molding (PIM), such as the packing pressure, the mold temperature, the melt temperature, and so on, are generally determined by a trial-and error method through the experiments. Computer-aided engineering (CAE) in the PIM is an alternative approach to determine the optimal process parameters. In cap-type plastic product, large volume shrinkage makes the clamping difficult. Furthermore, small clamping force leads to high productivity as well as cost reduction. Both volume shrinkage and clamping force should then be minimized simultaneously, and a multi-objective design optimization is formulated. Inappropriate process parameters easily lead to short shot that the melt plastic is not fully filled into cavity. In this paper, short shot is handled as the design constraint. Numerical simulation of the PIM is so expensive that the response surface approach is valid. In particular, a sequential approximate optimization (SAO) that the response surface is repeatedly constructed and optimized with some new sampling points is recognized as one of the most powerful tools available. In this paper, the radial basis function (RBF) network is adopted for the SAO, and the pareto-frontier is identified with a small number of simulation runs. Numerical result shows that the pareto-frontier is well identified with a small number of simulation runs.     

基于CAE技术的注塑模组合型腔流动平衡设计及工艺分析

利用注塑模CAE软件Moldflow Insight 2010对结构复杂的组合型腔制件进行了流动、充填和流道平衡模拟分析,确定了单浇口组合型腔浇注系统布置方案,优化了特定条件下可使二型腔平衡进料的浇注系统尺寸。采用综合平衡法设计正交试验并开展CAE模拟实验,通过对因素与水平的直观分析,讨论了模具温度和熔体温度等工艺对注塑成型中流动平衡的影响,并给出了特定条件下工艺参数的最优组合。     

Visualizing analysis for weld line forming in micro injection molding by experimental method

In micro injection molding, the melt flow behavior is important for the final product quality. However, the current process monitoring and measurement technology are not adequate enough to provide a direct analysis access. In the presented study, a glass insert mold designed for performing the direct visual analysis for melt flow phenomena in micro injection molding is introduced. The micro tensile specimen with 0.1 × 0.4 mm² (depth × width) cross section dimension is chosen as the objective part. The correlation between processing parameters (injection pressure, injection speed, mold temperature) and flow behavior was investigated and analyzed. The results show that the injection pressure put an obvious effect on the filling speed through micro cavity. Injection speed can influence the filling time dramatically also. Higher mold temperature brings positive influence with the flowing speed, due to the lower viscosity of polymers in higher mold temperature.     

Parametric design and process parameter optimization for bra cup molding via response surface methodology

Seamless and traceless undergarments have rendered foam sheet molding as an important manufacturing technique for the intimate apparel industry. Seamless bra cups are made by one-step forming technology. The three-dimensional (3D) cup shape is formed by using high temperatures and pressures with flexible polyurethane foams. Nevertheless, the mold head design process and control of the bra cup molding process are highly complicated and error prone. There is limited knowledge about the effects of foam properties, molding parameters and foam cup geometric parameters on molding process optimization. This research presents a response surface methodology as the approach for parametric design and process parameter optimization of bra cup molding. The proposed approach integrates 3D scanning via reverse engineering, parameterized-based remeshing and registration algorithm, non-linear mathematical prediction models for cup shape conformity, a model of foam shrinkage and example-based bra cup design and grading to optimize the bra cup development and production process. The experimental results show that this method is highly effective and more timesaving in the design and development of new products, as well as providing consistent quality control of the bra cup molding process.     

Correction to: Numerical simulation and experimental analysis of the sintered micro-parts using the powder injection molding process

Microsystem Technologies - Unfortunately, one of the co-author’s family name was incorrect in the original online publication of this article. The correct family name should be:     

Layered tetrahedral meshing of thin-walled solids for plastic injection molding FEM

This paper describes a method for creating a well-shaped, layered tetrahedral mesh of a thin-walled solid by adapting the surface triangle sizes to the estimated wall thickness. The primary target application of the method is the finite element analysis of plastic injection molding, in which a layered mesh improves the accuracy of the solution. The edge lengths of the surface triangles must be proportional to the thickness of the domain to create well-shaped tetrahedrons; when the edge lengths are too short or too long, the shape of the tetrahedron tends to become thin or flat. The proposed method creates such a layered tetrahedral mesh in three steps: (1) create a preliminary tetrahedral mesh of the target geometric domain and estimate thickness distribution over the domain; (2) create a non-uniform surface triangular mesh with edge length adapted to the estimated thickness, then create a single-layer tetrahedral mesh using the surface triangular mesh; and (3) subdivide tetrahedrons of the single-layer mesh into multiple layers by applying a subdivision template. The effectiveness of the layered tetrahedral mesh is verified by running some experimental finite element analyses of plastic injection molding.     

Neural‐network‐based predictive controller design: An application to temperature control of a plastic injection molding process

This paper presents a neural‐network‐based predictive control (NPC) method for a class of discrete‐time multi‐input multi‐output (MIMO) systems. A discrete‐time mathematical model using a recurrent neural network (RNN) is constructed and a learning algorithm adopting an adaptive learning rate (ALR) approach is employed to identify the unknown parameters in the recurrent neural network model (RNNM). The NPC controller is derived based on a modified predictive performance criterion, and its convergence is guaranteed by adopting an optimal algorithm with an adaptive optimal rate (AOR) approach. The stability analysis of the overall MIMO control system is well proven by the Lyapunov stability theory. A real‐time control algorithm is proposed which has been implemented using a digital signal processor, TMS320C31 from Texas Instruments. Two examples, including the control of a MIMO nonlinear system and the control of a plastic injection molding process, are used to demonstrate the effectiveness of the proposed strategy. Results from both numerical simulations and experiments show that the proposed method is capable of controlling MIMO systems with satisfactory tracking performance under setpoint and load changes. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Fabrication of the plastic component for photonic crystal using micro injection molding

In this decade, many techniques have been introduced to fabricate photonic crystal in optical applications. Most of the processes used to fabricate the photonic crystal are time consuming and not cost effective. This study demonstrates an efficient method to fabricate photonic crystals. A polymer-based photonic crystal slab has been developed by embedding mixture with a high dielectric constant. Photonic crystals have patterned structures in which periodicity of dielectric properties can manipulate electromagnetic waves. The operation wavelength is about half of the characteristic dimension. Technique of injection molding is applied to make polymer parts with the photonic crystal pattern. Then mixture of barium titanate powder and epoxy is embedded on the patterned structure of the polymer part. The contrast of dielectric coefficients between mixture and polymer can constitute a structure with some photonic band gap. By means of polymer processing, mass production of photonic crystal devices like optical switch, optical waveguide, optical filter and so forth can be realized in a cost effective way.     

模流分析在汽车注塑件设计中的应用

鉴于越来越多的注塑部件应用于汽车设计,而注塑产品的熔接线通常是强度最薄弱的区域,因此对熔接线的预测和优化非常重要。以某汽车前端模块为实例,阐述借助Moldflow快速找到改善熔接线质量的解决方案。经Moldflow分析发现,当浇口位置和数量不变时,优化产品的局部料厚可以明显提高熔接线的质量。     

车用塑料件的模流与结构联合仿真分析

现存结构仿真软件的材料模型无法准确表达塑料及纤维复合材料零件各向异性的特性,为提高这类零件结构仿真的准确性,使用Moldex3D,Digimat和OptiStruct联合仿真的方法,针对汽车空调风门进行三点弯曲试验工况下的强度仿真与分析。按照实际成型工艺对空调风门进行模流分析,将模流分析得到的结果通过Digimat映射到结构有限元模型上,得到联合仿真模型,并将该模型的分析结果和未映射模型的分析结果同时与通过试验获得的真实应力值进行对比分析。研究结果表明：由成型工艺导致的材料各向异性对风门的应力分布和重点区域应力值均有较大影响;在熔接线附近,考虑玻纤取向的联合仿真模型得到的应力值与实际的应力值更接近,可以提高含玻纤材料零件仿真计算结果的准确性。     

Integrated modeling, finite-element analysis, and engineering design for thin-shell structures using subdivision

Many engineering design applications require geometric modeling and mechanical simulation of thin flexible structures, such as those found in the automotive and aerospace industries. Traditionally, geometric modeling, mechanical simulation, and engineering design are treated as separate modules requiring different methods and representations. Due to the incompatibility of the involved representations the transition from geometric modeling to mechanical simulation, as well as in the opposite direction, requires substantial effort. However, for engineering design purposes efficient transition between geometric modeling and mechanical simulation is essential. We propose the use of subdivision surfaces as a common foundation for modeling, simulation, and design in a unified framework. Subdivision surfaces provide a flexible and efficient tool for arbitrary topology free-form surface modeling, avoiding many of the problems inherent in traditional spline patch based approaches. The underlying basis functions are also ideally suited for a finite-element treatment of the so-called thin-shell equations, which describe the mechanical behavior of the modeled structures. The resulting solvers are highly scalable, providing an efficient computational foundation for design exploration and optimization. We demonstrate our claims with several design examples, showing the versatility and high accuracy of the proposed method.