The application of modified viscoplastic constitutive relationship on the warpage prediction of injection-molded part (original) (raw)
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A viscoplastic constitutive model for polymeric materials
International Journal of Plasticity, 2008
Classical models based on the thermodynamics of irreversible process with internal variables dedicated to the inelastic analysis of metallic structures are modified and then used for modeling the mechanical behavior of polymers. The major difference comes from the expression of the yield criterion. Indeed, a generalized yield criterion, based on the parabolic Drucker and Prager criterion, is proposed including the first invariant of the stress tensor as well as the second invariant and the third invariant of the deviatoric part of the stress tensor. Close agreement between experimental data and yielding predictions is obtained for various polymers loaded under different states of stress. It has been established that the temperature T, the strain rate _ s, the critical molecular mass M c and the degree of crystallinity X c do not affect the parameter m of the proposed yield function. Furthermore, viscoplastic constitutive equations are developed in the framework of the general principles of thermodynamics with internal variables for generalized materials considering only the kinematic hardening rule. Experimental data obtained under different loading conditions are well reproduced by the proposed model. An accurate identification of the model parameters and the introduction of the isotropic hardening variable into the yield function and the drag stress will improve the predictions of the overall mechanical behavior of polymers especially the unloading path.
Shrinkage and warpage prediction for injection molded components
Shrinkage and warpage analysis is now an important part of Computer Aided Engineering (CAE) for injection molded components. The theory behind this analysis (including effects of crystallinity, orientation and cooling stress relaxation) is presented, along with a number of case studies showing the successful application of this technology.
Improvement of warpage prediction through integrative simulation approach for thermoplastic material
Journal of Thermoplastic Composite Materials, 2020
In the injection-molded parts, prediction of accurate warpage at initial level becomes mandatory to avoid iterative work of mold modifications. Simulation teams of many organizations are using existing commercial programs for process simulations. Material models in existing simulation technologies are having certain limitations and assumptions, which can regularly result in up to 50% variation of warpage results as compared to the actual physical warpage measurement. The commonly used Moldflow simulation model, for example, ignores temperature-dependent mechanical properties and the stress relaxation spectrum for viscoelastic materials. These assumptions affect the accuracy of the warpage prediction results significantly. To decrease these kinds of variations, BASF extended its Ultrasim® tool which is based on integrative simulation technology. Recently, a newly developed thermomechanical material model with temperature-dependent nonlinear mechanical properties and stress relaxation...
IDENTIFICATION OF CRIMS MODEL PARAMETERS FOR WARPAGE PREDICTION IN INJECTION MOULDING SIMULATION
2010
Polymer injection moulding is a process widely used to produce components in a lot of different applications. One of the most critical aspects related to this process is to control the warpage of the parts after the extraction from the mould. Numerical simulations can predict a part warpage by using specific warpage models. Among numerical codes, Autodesk Moldflow Insight ® uses a Corrected In Mold Residual Stress (CRIMS) model, that calculate the residual stresses develop during the moulding process. Warpage is then predicted calculating the deformations of the component induced by the considered stresses. Using experimental and numerical techniques, a new identification procedure was introduced to evaluate the six parameters of the CRIMS model included in the Moldflow ® material properties database. The study was conducted on a box for an automotive application made of polypropylene. On the base of a complete rheological, thermal and physical characterization of the employed material, a numerical simulation of the process was implemented, integrating it with an optimization procedure to identify the values of the CRIMS parameters that force numerical results to fit measured deformations. As this procedure was very time consuming, requiring to run several computationally intensive simulations, artificial neural networks were employed to approximate numerical results with lower computational time. Results were verified with independent samples, showing good correspondence between experimental results and numerical calculated deformations.
Effect of CaCO3 Additive on the Warpage of Injection Molding Part
Universal Journal of Mechanical Engineering, 2014
In injection molding process, improving the part quality by reducing the warpage is an issue, especially with the thin-walled product. In this paper, the injection molding process was applied to a rectangular plate of 150 mm x 30 mm. The part thickness was varied from 1.0 mm to 2.5 mm. Three types of material as polypropylene (PP), acrylonitrin butadiene styrene (ABS), and polyvinyl chloride (PVC) were selected for observing the influence of volume shrinkage ratio on the warpage. Then, different weight ratios of CaCO 3 (10%, 20%, 30%, and 40%) additive were mixed with the PP material and then, the mixture was molded. The result shows that the volume shrinkage ratio of plastic material has a strong influence on the part warpage with the thickness of 1.0 mm, 1.5 mm, and 2.0 mm. However, with the thickness of 2.5 mm, the different warpage under three types of plastic is not strongly. With the CaCO 3 , the result shows that the more the CaCO 3 additive, the lesser is the part warped. However, with a thickness of 2.5 mm, the CaCO 3 has a negative influence on the warpage. In addition, this research was achieved by both simulation and experiment. The comparison shows that the simulation result and experiment result agree well.
The Effect of Pressure on Warpage of Dumbbell Plastic Part in Injection Moulding Machine
Advanced Materials Research, 2014
The optimization of processing parameters on warpage of polypropylene (PP) in the application of injection moulding machine was studied. The appropriate parameters were adjusted to reduce the warpage defect on the tensile test specimen of dumbbell. The type of injection moulding machine used in this research is Arburg 420C 800-250C. Four parameters that have been investigated; injection pressure, clamping pressure, back pressure and holding pressure. A concept of design of experiment (DOE) has been applied using Taguchi method to determine the suitable parameters. To measure the warpage of the dumbbell, digital height gauge was used to measure the flatness of the part surface. According the analysis of variance (ANOVA), the most significant factor that effect the warpage was holding pressure by 57.82%, followed with back pressure by 25.75%, clamping pressure by 16.27% and injection pressure by 0.16%. It is found that the optimum parameters setting that have been obtained were injection pressure at 950 bar, clamping pressure at 600 kN, holding pressure at 700 bar and back pressure at 75 bar. The depreciation value of warpage minimum index in this experiment was decreased by 4.6% after confirmation run.
SAE International Journal of Materials and Manufacturing, 2013
Blow moulding is one of the most important polymer processing methods for producing complex thermoplastic automotive parts. Contrary to injection molding, little attention has focused on process control and simulation of blow molding processes. Yet, there are still several problems that affect the overall success of forming these parts. Among them are thermally induced stresses, relevant shrinkage and part warpage deformations caused by inappropriate mold design and/or processing conditions. Tolerance issues are critical in automotive applications and therefore part deformation due to solidification needs to be controlled and optimized accordingly. The accurate prediction tool of part deformation due to solidification, under different cooling conditions in automotive formed parts, is important and highly suited for part designers to help achieve an efficient production. This paper describes in detail the three dimensional membrane element in large displacement formulation with an integration and implementation of the KBKZ constitutive equation to model the blowing phase of forming processes. Thereafter, we focus on the development of a linear thermo-viscoelastic constitutive equation based on a Zener model for modeling shrinkage and warpage of molten-solidified polymeric material during the cooling and solidification. The derivation of the governing equations as well as the implementation in our BlowView software is discussed and presented. The finite element method (FEM) will be used to numerically solve the derived governing equations and the shell theory, presented as an assemblage of flat elements formed by combining the Constant Strain Triangle element (CST) and Discrete Kirchhoff plate theory (DKT element), is applied. This shell theory is well suited for thin complex blow molded automotive parts. The numerical implementation and integration in BlowView is presented in detail. Finally, finite element warpage simulation results in terms of displacements and deformations, obtained with this formulation are presented for a simple and complex automotive part. The simulation results are compared to experimental and literature results to determine the accuracy and the limitations of the proposed model.
Warpage Prediction in Plastic Injection Molded Part using Artificial Neural Network
2013
The Main objective of this paper is predicting the warpage of a circular injection molded part based on different processing parameters. The selected part is used as spacers in automotive, transmission, and industrial power generation industries. The second goal is facilitating the setup of injection molding machine without (any) need to trial and error and reducing the setup time. To meet these objectives, an artificial neural network (ANN) model was presented. This model is capable of warpage prediction of injection molded plastic parts based on variable process parameters. Under different settings, the process was simulated by Moldflow and the warpage of the part was obtained. Initially, the effects of the melt temperature, holding pressureand the mold temperature on warpage were numerically analyzed. In the second step, a group of data, which had been obtained from analysis results, were used for training the ANN model. Also, another group of data was applied for testing the amount of ANN model prediction error. Finally, maximum error of ANN prediction was determined. The results show that the R-Squared value for data used for training of ANN is 0.997 and for the test data, is 0.995.
Analysis of Warpage and Shrinkage for an Injection Molded Component Using Flow Analysis Software
IAEME PUBLICATION, 2013
Plastic Injection molding industry has been playing a major role in the mass production of plastic products for various industries; here a product from electrical industry is taken and studied for its quality improvement. This Study deals with the application of Computer-aided Engineering integrating with statistical technique to develop an injection molded Electrical Product with a reduced warpage and shrinkage which is considered as serious quality defects. For this purpose, the optimum injection molding processing parameters were found by conducting number of flow analyses using Moldex 3D software. The various combination of parameters were selected by following the L27 orthogonal array, the optimization methodology of Taguchi, experimental design and analysis of variance (ANOVA) were used to predict the optimum and significant process parameters inducing the warpage and shrinkage. Statically it is concluded that Packing Pressure and Melt temperature were found to be the most significant parameters, while the mold temperature had the least effect on the warpage and shrinkage for this product. Furthermore effect of variation of significant parameters on the warpage and shrinkage are also studied.