Three-dimensional finite element method for the filling simulation of injection molding

With the development of molding techniques, molded parts have more complex and larger geometry with nonuniform thickness. In this case, the velocity and the variation of parameters in the gapwise direction are considerable and cannot be neglected. A three-dimensional (3D) simulation model can predict the filling process more accurately than a 2.5D model based on the Hele–Shaw approximation. This paper gives a mathematical model and numeric method based on 3D model to perform more accurate simulations of a fully flow. The model employs an equal-order velocity–pressure interpolation method. The relation between velocity and pressure is obtained from the discretized momentum equations in order to derive the pressure equation. A 3D control volume scheme is used to track the flow front. During calculating the temperature field, the influence of convection items in three directions is considered. The software based on this 3D model can calculate the pressure field, velocity field and temperature field in filling process. The validity of the model has been tested through the analysis of the flow in cavities.     

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.     

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.     

Electro-optical properties of a twisted hybrid aligned nematic mode for reflective liquid crystal displays

Abstract— A twisted hybrid aligned (THA) mode is proposed for reflective liquid-crystal displays. In the reflective configuration, a single polarizer and a reflective electrode are used to achieve electrooptical switching between the black and white states in the THA mode of a chiral nematic liquid crystal. Numerical simulations are performed to optimize the cell parameters such as the cell thickness and the amount of the twist in the hybrid geometry. The reflective THA mode is found to give wider viewing and faster response characteristics than a twisted nematic one. The role of an optical retardation film on device performance of such a reflective THA cell is also discussed.     

A composite model for accurate colorimetric characterization of liquid crystal displays

This paper presents a composite color‐characterization model for Liquid Crystal Displays (LCDs), considering channel dependence and poor chromaticity constancy of primaries. The proposed model consists of two parts, that is, the Piecewise Linear assuming Variation in Chromaticity (PLVC) model and a partition compensation error model. PLVC model can accurately predict CIEXYZ for primaries and calculate the CIEXYZ of any digital input values ( d _r , d _g , d _b ) based on the channel independence assumption. In addition, the prediction error of PLVC model is compensated in RGB subspace using the partition compensation error model. The color difference Δ was used to evaluate the accuracy of the model. The result of this experiment shows that PLVC model performs well for LCDs with channel independence and poor chromaticity constancy of primaries, compared with other characterization models. For channel dependence and poor chromaticity constancy LCDs, our result shows that proposed composite color‐characterization model also has better prediction accuracy than all other tested models. In this study, measurements were conducted in ambient light environment, and the experiment results consist with practical applications.     

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.     

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.     

Application of artificial neural network and fuzzy logic in a case-based system for initial process parameter setting of injection molding

Determination of initial process meters for injection molding is a highly skilled job and based on skilled operators know-how and intuitive sense acquired through long-term experience rather than a theoretical and analytical approach. Facing with the global competition, the current trial-and-error practice becomes inadequate. In this paper, application of artificial neural network and fuzzy logic in a case-based system for initial process meter setting of injection molding is described. Artificial neural network was introduced in the case adaptation while fuzzy logic was employed in the case indexing and similarity analysis. A computer-aided system for the determination of initial process meter setting for injection molding based on the proposed techniques was developed and validated in a simulation environment. The preliminary validation tests of the system have indicated that the system can determine a set of initial process meters for injection molding quickly without relying on experienced molding personnel, from which good quality molded parts can be produced.