The SPE Library contains thousands of papers, presentations, journal briefs and recorded webinars from the best minds in the Plastics Industry. Spanning almost two decades, this collection of published research and development work in polymer science and plastics technology is a wealth of knowledge and information for anyone involved in plastics.
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How To Use CAE To Diagnose The Under-Performance Problem Of The Existed Machine In Injection Molding To Face Automation Challenge
Recently, many automation technologies and equipment are applied for new injection molding systems to execute automation for Industry 4.0. However, there are also a huge numbers of the existed injection machines or systems which are not ready for automation yet. Indeed, before automatic manufacturing, how to retain good quality is one of the crucial factors in injection molding. In this study, we have focused on how to discover the under-performance problem of some existed injection machine to face the automation challenge using CAE technology. In the real testing case, we have demonstrated that CAE simulation prediction can be regarded as the ideal target for manufacturing. Furthermore, it is also estimated the difference between simulation prediction and real experimental result quantitatively. However, after careful comparison on the amount of the driving force to generate deviation from the target, the real experimental result presents almost the same trend and the same amount as numerical prediction did. Moreover, we also tried to compensate the under-performance of the real experiment using a series of packing pressure settings suggested by numerical simulation. Results showed that quality can be improved significantly.
Deep Learning On Cae Based On The Integration Of The Taguchi Method And Neural Network
Plastic injection molding has become an important technique in traditional industry in recent years. In the process of injection molding, many manufacturers rely on the experiences of skilled workers, rather than utilizing an efficient method to eliminate processing defects, resulting in difficulties in quality control and increased total cost. To solve the problem of defect removal effectiveness, computer-aided engineering (CAE) is often employed, which can eliminate molding defects, through simulation analysis, before manufacturing. However, some unpredictable problems remain during the actual molding, which require the assistance of field technicians.The outcomes of injection molding, which involve injection pressure, cooling time, and warping deformation, have an intricate connection with control factors, which cannot be classified by regular linear programming. Back Propagation Neural Network (BPNN) has excellent predictive ability in solving non-linear problems. It can accurately predict the results after executing a series of training data. This study combined the orthogonal Taguchi Method and BPNN to construct a computing system for predicting the analysis result of CAE, and analyze the influence of multi-layer structure on prediction accuracy. The results showed that using the Taguchi Method to optimize the parameters of BPNN can increase the accuracy of prediction. Using the optimized network parameters can reduce the prediction error of the maximum injection pressure and maximum cooling time to less than 1%. However, there is still an error of 7.26% for the prediction on warping deformation, which demands further investingation of training data.
Simulation Study Of Injection Compression Moulding Process For A 0.6Mm Thin Polymeric Microfluidic Chip
Thin polymeric microfluidic chip design (chip thickness 0.6mm or less) is desired for lab-on-chip device due to rapid heat transfer across thickness direction. This feature results in better bonding property and temperature control during diagnostic analysis. It also offers good optical properties for the observation of fluidic mixing, filtering and reaction in the multi-layer and multi-functional chip design. However, polymer melt filling for thin chip poses great challenges as the frozen layer along melt flow path is built up rapidly for conventional injection moulding process. Some moulding defects may associate with thin chip design such as short shot, warpage, thickness variation and birefringence etc. In this paper, a series of Moldflow simulation studies were conducted to virtually investigate the effects of thin chip melt filling characteristics for both conventional injection moulding (CIM) and injection compression moulding (ICM) processes. The simulation results show that injection compression process is an enabling moulding technique for a polycarbonate (PC) based 0.6mm polymeric micro reactor chip design. Compared to CIM process, there is more than 30% improvement on chip micro feature replication accuracy and chip deflection.
How Poor Design Can Severely Limit Materials, Tooling And Processing Capabilities
This is an invited paper for the Join IMD-PD3 Session.For a plastic part or assembly to perform as expected, proper consideration must be given to material selection, part design, tooling, and processing. In many instances, design errors are misclassified as tooling, processing or material issues. It is also not uncommon to attribute design related failures to customer abuse! As an example, a sharp transition in the wall thickness can cause:- Flow marksMisclassified as poor gate design or location, inadequate cooling, too little or too much holding pressure, high injection speed causing chain breakdown or pigment degradation, contamination, etc.- Poor chemical resistance and cracks Misclassified as the chemical resistance of the material- Failure in dropMisclassified as processing issues causing high molded stresses, material weakness, customer abuse, etc.- WarpageMisclassified as uneven packing pressures, poor cooling, etc.Numerous actual parts will be shown to illustrate the foregoing.
Using Magneto-Archimedes Levitation For Non-Invasive Characterization Of Injection Molded Parts
In a magneto-Archimedes levitation device, a three-dimensional (3D) injection molded part can be levitated with a posture that is closely related to its shape and internal defect. Here, a novel, non-invasive characterization method for 3D injection molded parts via magneto-Archimedes levitation is proposed. FLUENT-EDEM multiphase software was used to simulate the levitation process of the 3D part. Through the results of the EDEM software, the curves of the levitation height, equilibrium posture, and potential energy versus simulation time were obtained. The final levitation height and the equilibrium posture of the part were determined by the principle of minimum potential energy. Several experiments with vari¬ous 3D parts and different internal defects were carried out to verify the proposed method. Experimental results showed that the proposed method had high accuracy in measuring equilibrium posture and levitation height. For defective parts with small voids (2 mm3), the maximum deviation between the calculated tilt angles and the exper¬imental results was less than 4.7°. In general, the proposed method has the potential of broad application in the non-invasive characterization of injection molded parts.
Using New Anisotropic Rotational Diffusion Model To Improve Prediction Of Short Fibers In Thermoplastic Injection Molding
In the article, we discuss a new fiber orientation model (Ci-D3) for prediction of fiber orientation in plastic composites during injection molding. We also compare fiber orientation predictions of the new model with: Folgar-Tucker (FT) and Reduced Strain Closure (RSC) with two different closure approximations (Hybrid and Orthotropic). Ci-D3 with Orthotropic closure approximation has shown predictions closest to the experiment followed by RSC with Orthotropic closure. Using Ci-D3 with Orthotropic instead of FT with Hybrid closure allows to halve average discrepancies between experimental measurements of fiber orientation and computer predictions.
Deformation And Stress Prediction Of Injection Molded Components After Being Mounted Into Designed Position
In many industrial applications such as automobiles,aircraft and home appliances, it is essential to meet tight dimensional tolerances after injection molded components are mounted into the designed position. The prediction of the final deformation and stress of the components after the assembly normally requires a combination of warpage analysis, an interface between warpage analysis and structural analysis and a separate structural analysis, as the process-induced and assembly-induced deformation are calculated sequentially. A much simpler approach is developed for predicting the final deformation and residual stress, which only requires a warpage analysis with specially calculated boundary constraints. It has been implemented in three widely-used modelling methods in injection molding simulation: the midplane shell model, dual-domain shell model and three-dimensional tetrahedral model. Two numerical examples are given to illustrate the effectiveness of the approach. This proposed approach provides an easy and valuable tool for predicting the amount of geometric deviation between the final mounted component and the original design.
Additive Manufacturing Of Large, Temperature-Controlled Injection Molding Tools Using Arc Welding And Diffusion Bonding
The temperature control of molding tools, in this case injection molding, plays a critical role in the quality of manufactured plastic articles. Key parameters such as shrinkage, warpage, crystallinity, etc. can be significantly influenced by the temperature control concept. Variothermal process control in particular delivers good results in terms of flow path length and part quality. For tools in the small to medium size range, these structures can be additively generated by methods such as selective laser sintering. For large workpieces however, such as automobile bumpers or containers, the currently available manufacturing technologies reach the limits of their geometry. Up to now, it has not been possible to additively manufacture such large-format tools while generating temperature control channels at the same time. This paper presents a method of manufacturing large-scale mold tools with temperature control channels by combining the additive manufacturing techniques of arc welding and diffusion bonding with conventional processes.
Inflation Behavior Of Preforms In The Special Injection Molding Process Gitblow Combining Gas Assisted Injection Molding And Blow Molding
The demand for innovation within the plastics industry has led to a large variety of specially adapted production processes. Meeting the requirements for lightweight and complex shaped part geometries the special injection molding process GITBlow was invented by the Kunststofftechnik Paderborn a few years ago. The process consists of the production of a preform via gas-assisted injection molding (GAIM) and a secondary gas injection for a further inflation of this preform within a larger cavity. In this paper the focus is set on the second gas injection and the inflation behavior of the preform. Despite the similarities between this step and conventional injection blow molding, there are some distinctive differences concerning the temperature level and temperature distribution prior to the inflation. In a systematic approach with several materials and process settings, a process characteristic strain rate profile is determined using a specially adapted mold. Using the laws of fluid dynamics, the measured profiles are analyzed in more detail.
Empirical Modeling And Simulation Of The Microstructure Replication In Injection Molding
Microstructured surfaces offer a high potential for use in the injection molding process. On the one hand, structures can be utilized to functionalize molded parts during the molding process and on the other hand, to manipulate the flow properties of the plastic melt in the mold. The following work addresses the development of an integrative simulation methodology, which will allow for predicting the replication quality of structures from steel to plastic part, thus enabling the efficient development of customized microstructures.The selected model approach achieved a good representation of the structure replication in plastics based on process settings and structure geometry. Furthermore, the main influencing factors on the structure replication were determined and statistically evaluated. Using this model and an integrative link to a commercial injection molding simulation software, it is already possible to predict the local degree of replication of microstructured surfaces.
Characterization Of Filling Performances And Mechanical Properties Of Micro Molded Features
The achievement of an adequate accuracy of the micro injection molding (μIM) process applied to the replication of micro-features is a complex task. The selection of parameters influences the filling performance as well as the replicated quality of micro-features and local mechanical property. In this paper, the relationship between process parameters, filling morphology of micro-features and mechanical property were investigated based on DOE method. It was found that the biggest contribution of process parameter to replicated quality for micro feature parallel to flow direction was hold pressure, while mold temperature had the most influence on replicated ability for micro feature perpendicular to flow direction. Local mechanical properties were also different between two arrangements of micro features and substrate in the same micro part. The micro feature with high filling height had a smaller modulus than that with low filling height. The modulus on substrate were bigger than that on micro features. Meanwhile, mechanical property on substrate had no relationship with the arrangement of micro features.
Studying Of Viscoelasticity On Warpage Validation
Warpage is an important indicator when evaluating the quality of an injection molding product. How to control the warp within tolerance is a critical issue concerned by designer and molder. Accurate computer aided engineering (CAE) warpage prediction helps designer to find the best design from different prototypes quickly at the beginning of development, decreasing the cost. However, the warpage is the final result affected by several factors during injection molding, for instance material, injection machine, part and mold design. Hence, an accurate warpage prediction must take these factors into consideration comprehensively. The real machine response is compared with filling pressure to verify whether the flow simulation is accurate enough as input parameter of following warpage prediction. Unlike linear warpage calculation simply based on material PVT property, Moldex3D solver considers material viscoelasticity to simulate the significant modulus change when polymer transits from rubbery phase to glassy phase. Together with in-mold constraint and free deformation after ejection in warpage calculation, the warpage prediction shows high agreement with real box product on three different materials, PS, PC and PP.
Foaming Uniformity Control Of High Weight Reduction Microcellular Injection Molded Thermoplastic Elastomer Using Gas Counter Pressure
The microcellular injection molding process is widely used in the automotive, packaging, sporting goods, and electrical parts industries. The Mucell® process offers many advantages such as material and energy savings, low cycle time, cost effectiveness, and dimensional stability of products. Thermoplastic Polyurethane (TPU) is a common material for molding the outsole of shoes because of its outstanding properties such as hardness, abrasion resistance, and elasticity.Though many shoe manufacturers have begun applying Mucell® processes to TPU midsoles manufacturing, in moving to mass production, problems remain. The main problem is the uniformity of the cell size in the midsole. The cell size is affected by injection process induced pressure drops which lower the cell size uniformity in different regions and reduce the bouncing properties of the material. To address this problem, gas counter pressure technology was used to achieve a uniform cell size distribution midsole in the Mucell® process in this study.
Verification Of Numerical And Practical Approach In Implementing Pvt Properties Of Polymer To Control To Control Shrinkage Quality Of Molded
Quality optimization is a common concern in injection-molded products. The relation between pressure, specific volume and temperature is a key property in polymer processing. Because of the unpredictability of this relationship, it is difficult to mold products while maintaining quality in volume production. Traditionally, the most common approach to troubleshooting is for an experienced operator to adjust parameters repeatedly. Based on the PVT theory, this study created a practical PVT control technology using an infrared temperature sensor with pressure sensor in the mold. This method was then used to investigate the effect of molding parameters on the controllability and optimization of product quality.Results show that the PVT curves are constant under consecutive molding cycles and reveal the effect of molding parameters on quality controllability. Specific volume is directly related to product properties such as shrinkage, weight, and warpage. Three control methods for optimizing product quality were also investigated. The dynamic PVT control method molds parts with the smallest total shrinkage, heaviest weight, and least warpage. For molding stability, the PVT control method maintains constant product weight, shrinkage, and warpage.
Evaluating The Through-Plane Conductivity Of Molded Parts Via Magnetic Field In The Injection Molding Process
As industries transition, the application of composite materials has expanded. Composite materials manufacturing processes and technologies have become a focus of technology research and development. For fiber composite materials, since the fibers affect product properties, controlling them is a key to improving product performance. In this study, conductive paths were formed by adding nickel-coated carbon fiber to give the products electrical conductivity. In combination with a permanent magnet mold, experiments were conducted to verify whether the external magnetic field had an effect on the fiber orientation during filling. In the experimental part, the external magnetic field was ineffective due to cooling. Therefore, injection molding parameters such as temperature (melt temperature, mold temperature) as discussed herein. To understand whether there is an external magnetic field for the fiber orientation tensor, the influence of different parameters on the fiber orientation tensor and the through-plane conductivity under the condition of external magnetic field are explored.
Mechanical Properties Of Polyamide 6/Zeolite Composites
Many researchers have investigated the effect of Nano- and Micro-scale materials on the mechanical properties of the thermoplastic polymers. Some researchers showed that adding small amount of some mineral material to polymers matrix may enhance their physical and mechanical properties. In this study polyamide 6/zeolite composites having 2.5, 5, and 7.5 phr of the zeolite were prepared using a twin screw extruder and injection molding process, and different mechanical properties of the composites were investigated. Our results show that adding zeolite particles to polyamide, leads to increase of tensile strength by the maximum of 33%. Also having 7.5 phr of zeolite particles in the polyamide matrix results on 61% increase on the strain to rupture, compared to the pure polymer.
Effect Of Stress Relaxation On Shrinkage And Warpage Of Injection Molded Parts
The residual stresses in the injection molding process are built up due to the restriction of thermal contraction during the process, coupled with the frozen layer growth with varying pressure history. The stress relaxation behavior of plastic materials complicates the stress field. A three-dimensional linear anisotropic thermo-viscoelastic residual stress model is developed for predicting the effect of stress relaxation on shrinkage and warpage of injection molded parts. Thermo-rheological simplicity is assumed for the material, and the viscoelastic master curve is fitted with a generalized Maxwell model. A time-temperature shift factor table over the range of temperatures which occur during the injection molding process is preferred over the WLF equation and Arrhenius equation due to its general applicability. Two numerical examples are given, and the simulation result comparison between the thermo-viscoelastic model and thermo-viscous-elastic model shows that stress relaxation reduces the molded-in residual stresses slightly, and has a modest impact on shrinkage and warpage. The validation cases also confirm that the simple thermo-viscous-elastic residual stress model is generally able to give a good qualitative and reasonable quantitative prediction of the final shrinkage, warpage and molded-in residual stresses.
Effect Of Injection Molding Condition On Mold Adhesion During Thermoplastic Polyurethane Injection Molding
Injection molding is one of popular approach for the mass-production of plastic products with complex geometries. Although it is convenient and cost-effective to manufacture goods, some issues such as warpage, quality fluctuation of injection molded part, surface defects, insufficient physical properties are still needed to overcome. During ejection stage, one of annoying issues called mold adhesion, which happens to the interface between molded part and cavity surface, makes molded part difficult to release from mold surface, and the defects such as distortion and crack also occur as serious mold adhesion effect arises. This phenomenon is familiar during thermoplastic polyurethane (TPU) injection molding process. There are numerous factors affected the mold adhesion level, including injection molding conditions, surface morphology, surface modification, rheological properties of molten polymer. In order to understand the effect of molding conditions on mold adhesion level, tensile mode mold adhesion tester was proceeded to quantitatively evaluate mold adhesion level. In addition, surface free energy measured on molded part surfaces was carried out to better understand the wettability. In experiment results, mold temperature and melt temperature both effect on mold adhesion level. Moreover, the responses of SFE on different mold adhesion level are apparent.
Effects Of Processing Parameters On Fiber Length Distribution And Tensile Strength Of Long Glass Fiber Reinforced Nylon66 Composites Molded Parts
This study investigates the effects of processing parameters on the tensile strength and fiber length distribution of long glass fiber reinforced nylon66 composites. This study carried out the injection experiment at different screw speeds in order to take the fiber breakage and length distribution as the basis for the setting of processing parameters. The effects of processing parameters on tensile strength of long glass fiber reinforced nylon66 composites (LGF-Nylon66) were then studied using a tensile test specimen mold with single /double gate design (part thickness of 1.8 mm and 3.6 mm).The experimental results show that increasing the screw speed leads to fiber breakage, shortens the fiber length, and thus affects the tensile strength of long glass fiber reinforced nylon66 composites molded parts. On the other hand, as the melt temperature and the mold temperature increase, the tensile strength also increases. In addition, SEM observation presents that the effect of fiber length and orientation distributions on the weldline tensile strength of the molded specimen is very obvious. These results also show that the interfacial adhesion is required to achieve a desired composite strength.
Zero Defect Manufacturing In Injection Compression Molding Of Polymer Fresnel Lenses
Fresnel lenses are polymer optics with reduced dimensions and higher illumination properties. Their structured profile involves high precision replication techniques when industrial scale manufacturing is concerned. Injection Compression Molding (ICM) is the state of the art replication technology to ensure mass production of polymer optics. The opportunity to perform a compression phase on the polymer melt while injected into the cavity, ensures a more homogenous replication of the part, enhancing birefringence and transparency amongall the optical properties. However, it is not common to find studies concerning the technological signature of ICM components. The optical transparency of polymer optics as long as the complexity of Fresnel lens profile, are big challenges for metrology making this knowledge expensive and rarely investigated. In this study, absolute dimensions of Fresnel lenses step heights are correlated with respect to ICM process conditions. In a first experimental plan, the effect of packing and compression is individually evaluated on two different materials. In the case compression is performed without packing, the form replication accuracy of the micro structures fails, showing deviations up to 10 times the nominal dimension. On a secondary experimental campaign, packing pressure and compression gap are optimized together to identify the most favorable replication condition. The results show a second order interaction between compression gap and packing pressure. The average replication increases by 1.4 % when both a high level of compression gap and packing pressure are selected.
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