Moldflow Software Research Articles

Design and development of a novel double-chamber syringe concept for venous catheterization

This paper presents the optimization process for the development of an innovative double chamber syringe. Several aspects are involved such as design, functionality, fluid-structure interaction and friction between solids.To assist in the development of this medical device, a numerical based methodology was developed and validated in order to predict the syringe´s functionality, as well as its production by injection molding. The mechanical and flow behavior, during the filling and administration of medicine and washing solutions, were numerically modelled using the commercial software ABAQUS and FLUENT, respectively. The injection molding process was analyzed using the software MOLDFLOW. The aim was to evaluate the feasibility of the proposed concept in terms of mechanical design, fluid flow and production process behavior. By highlighting critical design issues in this way, it was possible to identify promising geometric changes and, consequently, optimize iteratively the syringe's design, until all the defined requirements are fulfilled.This iterative process based on numerical simulations proved to be a powerful tool for product development that generated fast and accurate results without the need to produce multiple prototypes.

Comparison of Real and Simulated Fiber Orientations in Injection Molded Short Glass Fiber Reinforced Polyamide by X-ray Microtomography.

During injection molding of short glass fiber reinforced composites, a complex structure is formed due to the fiber movement. The resulting fiber orientation can be predicted using various simulation models. However, the models are known to have inadequacies andthe influence of process and model parameters is not clearly and comprehensively described. In this study, the aforementioned model and process parameters are investigated to determine the dependencies of the individual influences on the real and simulated fiber orientation. For this purpose, specimens are injection molded at different process parameters. Representative regions of the specimens are measured using X-ray microtomography and dynamic image analysis to determine the geometric properties of the fibers as well as their orientations. Furthermore, simulations are performed with the simulation software Moldflow® using different mesh types and densities as well as varying parameters of the MRD model to represent the real fiber orientations. The results show that different orientation areas arise in the samples, which cannot be represented with a simulation varying only one parameter. Several simulations must be carried out in order to represent flow regions occurring in the specimen as realistically as possible.

Design, Optimization and Validation of Conformal Cooling Technique for Additively Manufactured Mold Insert

Injection molding is a cyclic process comprising of cooling phase as the largest part of this cycle. Providing efficient cooling in lesser cycle times is of significant importance in the molding industry. Conformal cooling is a proven technique for reduction in cycle times for injection molding. In this study, we have replaced a conventional cooling circuit with an optimized conformal cooling circuit in an injection molding tool (mold). The required heat transfer rate, coolant flow rate and diameter of channel was analytically calculated. Hybrid Laser powder bed fusion technique was used to manufacture this mold tool with conformal channels. The material used for manufacturing mold was maraging steel (M300). Thermal efficiency of the conformal channels was experimentally calculated using thermal imaging. Autodesk MoldFlow software was used to simulate and predict the cooling time required using conformal cooling channels. The results showed a decrease in cooling time and increase in cooling efficiency with the help of conformal cooling in additively manufactured mold insert.

Numerical Simulation and Process Optimization of a 3D Thin-Walled Polymeric Part Using Injection Compression Molding

Abstract Injection compression molding (ICM) is a hybrid injection molding process for manufacturing polymer products with high precision and surface accuracy. In this study, a 3D flow simulation was employed for ICM and injection molding (IM) processes. Initially, the process parameters of IM and ICM were discussed based on the numerical simulations. The IM and ICM processes were compared via numerical simulation by using CAE tools of Moldflow software. The effect of process parameters of mold surface temperature, melting temperature, compression force and injection time on clamping force and pressure at the injection location of molded 3D BJ998MO Polypropylene (MFI 100) part was investigated by Taguchi analysis. In conclusion, it was found that the ICM has a relatively lower filling pressure than ICM, which results in reduced clamping force for producing a 3D thin-walled polymeric part.

Influence of mold design and injection parameters on warpage deformation of thin-walled plastic parts

Thin-walled plastic parts are susceptible to deformation during injection molding. Using the example of a notebook battery cover, optimization of the injection mold design and injection process parameters was performed with Moldflow software, which resulted in about 69% reduction of the deformations. Moreover, the uneven material shrinkage during the injection process has been shown to be the main cause of deformations of thin-walled plastic parts.

Multi-objective optimization of GFRP injection molding process parameters, using GA-ELM, MOFA, and GRA-TOPSIS

Owing to the influence of the injection molding process, warpage and volume shrinkage are two common quality defects for products manufactured by glass fiber-reinforced plastic (GFRP) injection molding. To minimize these two defects, an extreme learning machine optimized with a genetic algorithm (GA-ELM), multi-objective firefly algorithm (MOFA), and a multi-objective decision-making method (GRA-TOPSIS) were implemented in this study. All of the experiments, based on Latin hypercubic sampling (LHS), were conducted using Moldflow software to obtain the results for warpage and volume shrinkage. The prediction accuracy of the defect-prediction models based on the extreme learning machine (ELM) and GA-ELM algorithms were compared. The results show that the GA-ELM models can better predict the defect values. Finally, MOFA was used to find the Pareto optimal front, and the GRA-TOPSIS method was used to find the optimum solution from the Pareto optimal front. According to the results of the simulation verification, the warpage and volume shrinkage were effectively reduced by 12.25% and 6.11%, respectively, compared with before optimization, which indicates the effectiveness and reliability of the optimization method.

Study and optimization of effective parameters in the occurrence of Blush defect in the plastic injection molding process by ANOVA

Plastic injection is one of the most important processes in plastic parts production. During this process, many defects can take place that affect products quality. This research focuses on decreasing one of these defects, called Blush. For this purpose, eight parameters with the probability of affecting the occurrence of this defect have been considered to be investigated. To study the effect or lack of effect, the extent, and the manner of effect of these parameters on the Blush defect, a Fractional factorial design of experiment with eight factors and two levels was performed. Then after finite element analysis in MoldFlow software and validation of analysis with experimental tests, the area of defect that occurred in each case was calculated by geometric methods. After ANOVA of the data, it was found that the parameters of runner diameter, holding pressure, flow rate, and melt temperature respectively, have the most significant effects on this defect. Then, for the four factors mentioned, an experimental design of Composite Cube Design was performed and after performing finite element analysis and analysis of variance on the data, it was found that all four parameters have a significant impact. It was also found that by increasing melt temperature, and holding pressure and reducing the runner diameter and flow rate to the optimal level, the area of blush defect will be reduced by 82.2%.

Numerical investigation on the influence of fiber orientation mapping procedure to the mechanical response of short-fiber reinforced composites using Moldflow, Digimat and Ansys software

Within this paper, a numerical study was performed, aiming to assess the influence of fiber orientation on the mechanical properties of tensile specimens, by using the finite element method. The specimen, designed according to ISO-527-2, is type 1BA and consists of a reinforced polyamide with 30% glass fiber (PA66 GF30). The specimens were extracted from 2 mm thickness plates, for which the fiber orientation tensor was determined using the dedicated Moldflow software for injection molding. The composite material was modelled using Digimat mean-field homogenization tool. The mechanical evaluation was performed in Ansys finite element software by coupling it with Digimat and thus considering the anisotropic behavior of the material. Different mapping procedures and mesh sizes for the Moldflow model and Ansys model were considered.

Simulation based characterization of recycled carbon fiber reinforced plastics in a rod specimen

Abstract This paper aims to characterize recycled carbon fiber reinforced plastics through simulations and predict the behavior of Polyamide 6 (Nylon 6) and Polypropylene (PP) when reinforced with short carbon fibers. By modeling ASTM 638D test specimen and simulating injection molding on Moldflow software, a fiber orientation factor was obtained. This factor was used to predict the tensile strength of the fiber reinforced plastics using modified Kelly-Tyson equation. Digimat software was further used to predict the young’s modulus and micro-analysis of the carbon fiber reinforced plastics. These mechanical properties were calculated for variations in the fiber content (by volume) and fiber length. An efficient CFRP recycling method and the corresponding characterization of the recycled composite can provide a solution to the problem of excessive carbon fiber waste generation and find newer applications for the recycled polymers, thus provide alternatives to the traditionally used materials.

Gate Optimization Analysis of Injection Molding for Mobile Phone Panel Based on Moldflow and Drop Simulation

Aiming at the gate design problem of a mobile phone panel, the plastic forming analysis software Moldflow and drop simulation were used to optimize the gate design. Six different gate design schemes were compared and studied, and the weld lines positions and injection molding results under each gate scheme were analyzed.Through the simulation analysis of the falling process of the mobile phone panel by the display dynamics analysis software ANSYS Workbench LS-DYNA, five analysis schemes were set according to the falling angle, and the stress distribution at the weld lines positions of the mobile phone panel in each scheme was studied. The reasonable gate scheme was given by synthesizing the force condition, the mold flow analysis and the drop simulation results of the mobile phone panel in use. Based on the results of die flow analysis and drop simulation the optimal gate design scheme 2 is found, and the weld line position avoids the lower part of the elliptical hole, which is the weak part of the structure. The research results had certain reference significance for the optimization of injection process of plastic products.

Experimental and Numerical Study Determining the Warpage Phenomenon of Thin-Wall Injection Molding

This study emphasizes the warpage phenomenon of thin-walled parts using acrylonitrile-butadiene styrene (ABS) plus polycarbonate (PC) plastics for optimal processing by thin-wall injection molding. The authors first employed the Moldflow software to analyze the runner’s balance on multicavities for thin-walled parts and to simulate the warpage of thin-walled parts with thin-wall injection molding. Then, this study used those data to fabricate a real mold by computer numerical control machining. For this study, the authors fabricated thin-walled parts and measured their warpage using various process parameters (injection speed, injection pressure, mold temperature, packing time, and melt temperature) with thin-walled injection molding. Finally, the authors found that the most important processing parameter was the packing time for warpage phenomenon of thin-walled parts by thin-wall injection molding.

A simulation-based approach for assessment of injection moulded part quality made of recycled olefins

To produce plastic parts of high geometrical quality and dimensional stability through injection moulding process there are several key variables that must be considered. These include processing parameters such as packing time, cooling time, packing pressure, melt temperature, mould temperature and the intrinsic melt flow characteristics of polymeric materials used to produce the part. The challenge of producing high quality part is further compounded if the input polymer material is of reclaimed waste streams with inherent inconsistency in their nature. In this work, significant number of simulation-based studies are conducted using Autodesk Moldflow software to delineate the contributing issues pertinent to the part quality and achieve topological optimization by reducing critical parameters of shrinkage and warpage while ensuring overall cycle time viable for industrial production rates. Key simulation variables were obtained through experimental characterization of flow and thermal properties of the recycled olefin plastics. Different gate locations were simulated, and the best gate locations were selected for a two-gate system. These gates were provided with gate valve controllers for controlling the polymer flow to create cascaded injection moulding scenarios. Such scenarios were iterated with the objective of reducing the pressure required for cavity filling and thereby reducing the clamp force required. Optimized melt and mold temperatures of 245 °C, 20 °C were used for all the simulations performed. The result obtained from the most optimized simulation showed an average cycle time of 10.42 secs, volumetric shrinkage of 5.08%, warpage of 1.05 mm and clamp force of 79.81 tonne would be required to produce a part of 200 mm*100 mm*1.5 mm dimensions. Following a cascaded injection setup, it was shown that the clamp force could be reduced by 60.57%.

Optimization and prediction of volume shrinkage and warpage of injection-molded thin-walled parts based on neural network

Warpage and volume shrinkage are important indicators of the quality of thin-walled parts during injection molding. In this study, the optimization goals are warpage and volume shrinkage. Design parameters include mold temperature, melt temperature, injection time, holding time, cooling time, and holding pressure. Based on the orthogonal experimental design and response surface experimental design, the MoldFlow software is applied to the simulation of the thin-walled part injection molding process. The importance of various parameters on warpage and volume shrinkage was analyzed by using analysis of variance. Based on the simulation results, a two-layer hidden-layer back propagation (BP) neural network model is established and the genetic algorithm (GA) is used to optimize the weights and thresholds of the back propagation neural network (BPNN) model to reduce warpage and volume shrinkage by optimizing the design parameters significantly. A support vector machine (SVM) combined with GA-BP was used to build a prediction model for predicting warpage and volume shrinkage. Taking the automobile wire harness protection frame as an example, and verified by numerical simulation, the GA-optimized two-layer hidden-layer BP neural network combination method is an effective method for injection molding to reduce warpage and volume shrinkage of thin-walled parts. SVM-BP-GA can accurately provide predictions for optimization goals; the amount of warpage and the volume shrinkage were 0.93% and 1.9%, respectively.

Development of Advanced Hybrid Polymer Melt Delivery Systems for Efficient High Precision Injection Molding

Abstract A novel melt manipulation “RheoDrop” concept for hot runner injection molding is presented. In this concept, a controlled rotational shear is applied to a polymer melt in the hot drop to reduce its viscosity without raising the temperature. This is achieved by providing a transient rotational motion to the valve pin in the hot drop. This strategy is developed to mitigate issues associated with cold slug formation during injection molding in hot runner systems. The cold slug formation is particularly relevant for injection molding of engineering plastics such as liquid crystal polymers (LCPs) for medical and electronic applications. Analytical and experimental investigations were performed to validate the concept. The efficacy of the concept is assessed analytically utilizing a combination of two software modules, autodesk, moldflow and ansys fluent. The results confirmed that the concept was able to produce enough shear to reduce the dynamic viscosity between injection molding cycles. A prototype RheoDrop system was designed and developed and retrofitted in a four drop hot runner system mold to experimentally validate the concept. Preliminary experiments were performed utilizing acrylonitrile butadiene styrene, and parts were successfully fabricated at temperatures that are too low for traditional molding in a hot runner system.

Multi-objective optimization of injection-molded plastic parts using entropy weight, random forest, and genetic algorithm methods

Abstract The qualities of injection-molded parts are affected by process parameters. Warpage and volume shrinkage are two typical defects. Moreover, insufficient or excessively large clamping force also affects the quality of parts and the cost of the process. An experiment based on the orthogonal design was conducted to minimize the above defects. Moldflow software was used to simulate the injection process of each experiment. The entropy weight was used to determine the weight of each index, the comprehensive evaluation value was calculated, and multi-objective optimization was transformed into single-objective optimization. A regression model was established by the random forest (RF) algorithm. To further illustrate the reliability and accuracy of the model, back-propagation neural network and kriging models were taken as comparative algorithms. The results showed that the error of RF was the smallest and its performance was the best. Finally, genetic algorithm was used to search for the minimum of the regression model established by RF. The optimal parameters were found to improve the quality of plastic parts and reduce the energy consumption. The plastic parts manufactured by the optimal process parameters showed good quality and met the requirements of production.

Simulation-Based Optimization of Plastic Injection Molding Parameter for Automotive Car Wheel Fabrication Using Response Surface Methodology (RSM)

In the era of revolution industry 4.0, most companies can expect metal-to-plastic conversion to result in cost savings. The objectives of this study are to find the most appropriate material composition and the injection molding process parameter to produce a plastic car wheel as a substitute for metal and aluminum alloy. The Polyetherimide (PEI) with different compositions are simulated using MoldFlow software and optimized the quality of injection molding process parameter by using Central Composite Design (CCD) in Response Surface Methodology (RSM) as to get an optimal response and meets the car wheel requirement specification. The crucial factors are melting temperature, injection time and cooling time. The quadratic model fits the model response. As the results, the optimum values suggested by the software were melt temperature of 370.27°C, 1.8s of injection time and 2599.89s of cooling time for 0% of filler (pure PEI). With small differences error value between solution and simulation, 0.1% of shrinkage and 0.9% for warpage, the results were acceptable.

Optimization Analysis of Correction Tape Box Compounding Cavity Runner Balance Based on Moldflow

Aiming at the problem of runner unbalance in the compounding cavity of the upper and lower cover of the correction tape box, the plastic injection analysis software Moldflow was used to optimize runner balance. First, the 3D modeling software Proe was used to establish the geometric model of the upper and lower cover of the correction tape box, and introduced into the plastic injection analysis software Moldflow. Secondly, the upper and the lower cover of the correction tape box were meshed and the initial gating system was designed in Moldflow. Filling analysis of the initial scheme of the correction tape box combined cavity showed that the runner of the melt was not balanced in the mold cavity. Finally, the runner balance optimization analysis of the cavities was carried out. Through optimization, the time unbalance rate of the melt in the mold cavity decreased from 28.6% to 0.7%, the pressure unbalance rate decreased from 42.0% to 4.2%, and the pressure distribution in the cavity was more uniform in the whole injection process.

Research on Changed Design of Gate Position of Window Frame of Automobile Front Door

The front door sash of the car is selected as the research object, and the design of the original gate position causes the warpage displacement of the front door sash to be large. Based on the CAE principle, using Molde×3D mold flow software analysis, it was found that the cause of the large amount of warpage deformation was flow imbalance. Then, according to the principle of flow balance, the design of the gate position was changed. The results of the mold flow analysis showed that the warpage displacement decreased from 18.5 mm to 14.1 mm, and the overall optimization was 24%. And the comparison found that the molding pressure was reduced from 224 MPa to 171 MPa (single cavity), and the clamping force was reduced from 2003 Ton to 1474 Ton (single cavity).

Simulation-Based Optimization of Plastic Injection Molding Parameter for Aircraft Part Fabrication Using Response Surface Methodology (RSM)

The small size and thin part characteristics of the honeycomb floor panel for the aircraft part product may cause problems in injection molding fabrication process. The objectives of this study is to find the most appropriate parameter in injection molding process for honeycomb floor panel by simulation using MoldFlow software and optimize the quality of injection molding process parameter by using Response Surface Methodology (RSM) as to obtain an optimal response and meets the requirement specification in the aviation scope. The crucial responses are shrinkage and warpage. Melt temperature, filling pressure and injection time are selected as the most influential factor for shrinkage and warpage. Model response was fitted by quadratic model. As the results, the optimum value suggested by the software were melt temperature of 360.02c, 60 MPa filling pressure and 4.70s injection time. With small differences error value between solution and simulation, 0.3% for shrinkage and 0.6% for warpage, the results was acceptable.

Minimum Warpage Prediction in Plastic Injection Process using Taguchi Method and Simulation

Plastic materials are used in automobile, electrical and electronic applications, agricultural utilization, household and furniture products, and medical equipments. Among various plastic manufacturing process, injection molding is one of the most commonly used and common methods applied for forming plastic products in the industry. The process requires a molten polymer being injected into a cavity of a mold, which is cooled and the product ejected from the mold. During the Plastic Injection Molding (PIM) process, various defects, such as volumetric shrinkage, warpage, weld line and sink mark can occur. This paper presents a method to minimizing warpage defect on PolyPropylene AZ564 via PIM simulation using Moldflow software. The approach was based on Taguchi method.Through the effectiveness of this proposed method, it is confirmed using simulation by Moldflow software. The effect of the process parameters on the warpage of a motorcycle number plate bracket, is studied using analysis of variance (ANOVA). From the ANOVA, the significant parameters affecting the process are holding time, holding pressure and injection pressure. The result of the Taguchi prediction shown that minimum warpage is 1.078 mm, which is 7.14% and 9.09% different from the simulation result and experiment, respectively.