This book covers a wide range of applications and uses of simulation and modeling techniques in polymer injection molding, filling a noticeable gap in the literature of design, manufacturing, and the ...use of plastics injection molding. The authors help readers solve problems in the advanced control, simulation, monitoring, and optimization of injection molding processes. The book provides a tool for researchers and engineers to calculate the mold filling, optimization of processing control, and quality estimation before prototype molding.
The quality control of plastic products is an essential aspect of the plastic injection molding (PIM) process. However, the warpage and shrinkage deformations continue to exist because the PIM ...process is easily interfered with by several related or independent process parameters. Thus, great efforts have been devoted to optimizing process parameters to minimize the warpage and shrinkage deformations of products during the last decades. In this review, we begin by introducing the manufacturing process in PIM and the cause of warpage and shrinkage deformations, followed by the mechanism about how process parameters, like mold temperature, melt temperature, injection rate, injection pressure, holding pressure, holding and cooling duration, affect those defects. Then, we summarize the recent progress of the design of experiments and four advanced methods (artificial neural networks, genetic algorithm, response surface methodology, and Kriging model) on optimizing process parameters to minimize the warpage and shrinkage deformations. In the end, future perspectives of quality control in injection molding machines are discussed.
Plastic syringes often rely on silicone oil lubrication to reduce plunger-barrel friction, leading to potential issues like oil droplet release and drug aggregation. This study explored an ...alternative approach combining two-photon polymerization, laser machining, and microinjection molding to manufacture micro-dimpled structures for low friction. Plastic microdimples with high area density and low aspect ratio significantly reduced the coefficient of friction against rubber, while the dimple profile proved crucial in facilitating replication and demolding. The results of this study provide valuable insights into reducing friction between rubber and plastic, particularly in applications like syringes.
•Precision plastic biaspheric lens having high and uneven thickness was developed using injection molding process.•A hybrid ANN and PSO technique was employed to predict the optimal process ...parameters.•Mould with aspheric profiles was prepared using single point diamond turning machine.•Surface characterisation like form, waveiness and surface roughness of mould and moulded bi-aspheric lens are measured.•Aberrations in the injection molded lens were studied using Shack-Hartmann Wavefront Sensor.
Injection molding of bi-aspheric lens using polycarbonate material with minimum variation in volumetric shrinkage is crucial for optical quality and is more challenging task among the researchers. In this paper, a hybrid artificial neural networks (ANN) and particle swarm optimization (PSO) technique is used to predict the optimal process parameters of injection molding process of the bi-aspheric lens. The developed ANN network (7-13-6) was trained as well as tested with experimental data sampled from statistical methods. The well trained and tested ANN network was coupled with improved PSO algorithm as a hybrid ANN-PSO to optimize the injection molding process parameters. The optimized injection molding process parameters obtained from hybrid ANN-PSO algorithm are validated with experiments using J. S. W injection molding machine. It is observed from the lens quality parameters that the proposed hybrid ANN-PSO method optimized the injection molding process of the bi-aspheric lens with an optical power of 27.73 Diopter and the lens posses seventh order spherical aberrations.
Double‐injection molding involves the use of two injection units, A and B, which can combine two different plastics into one part in a single injection molding process. Double‐injection molding can ...promote the recycling of plastic waste as well as improve the performance and dull appearance of plastic products made from recycled materials. However, the warpage of parts is a significant challenge in double‐injection molding. Warpage is significantly affected by the properties of the recycled material and injection molding process. In this study, the relationship between the warpage of double‐injection‐molded parts using raw and recycled materials was studied through uniform design experiments. To investigate the processes and warpage, the material was recycled several times, and its properties were tested. A regression model was established to describe the quantitative relationship between the important parameters and warpage. The number‐average molecular weight and weight‐average molecular weight exhibited the largest decrease after the first recycling cycle with a 21.11% and 41.11% decrease, respectively. The melting temperature decreased from 164.61 to 159.35°C, and the crystallinity did not change significantly. The processing parameters varied with the change in the properties of PP recycled materials, with the melt temperature decreased from 225 to 210°C. In addition, the number of recycling cycles and holding time for B were the most important factors influencing the warpage of double‐injection‐molded parts, followed by holding time for A and melt temperature for A. Warpage can be reduced by increasing holding times B and A. The experimental results provide important data for reducing the warpage of double‐injection‐molded parts with recycled materials.
Highlights
Double‐injection‐molded parts containing recycled materials were prepared.
Recycling enhanced the filling capacity of polypropylene.
The regression model of warpage with variables was established.
Warpage can be improved by adjusting processes and materials.
The effects of recycled materials and injection molding process on warpage in double‐injection molding.
Injection molding is a popular production process for short fiber reinforced components. The mechanical properties of such components depend on process-induced fiber orientations which are commonly ...predicted via numerical simulations. However, high computational costs prevent process simulations from being used in iterative procedures, such as topology optimization or finding optimal injection locations. We propose a fast approximation method that extracts nodal features and train a regression model to predict fill states, cooling times, volumetric shrinkage, and fiber orientations. The features are determined by solving eikonal equations with a fast iterative method and computing spatial moments to characterize node-adjacent material distributions. Subsequently, we use these features to train feed forward neural networks and gradient boosted regression trees with simulation data of a large dataset of geometries. This approach is significantly faster than conventional methods, providing 20x speed-up for single simulations and more than 200x speed-up in gate location optimization. It generalizes to arbitrary geometries and injection locations.
In this paper, cooling performance of conformal cooling channel in plastic injection molding (PIM) is numerically and experimentally examined. To examine the cooling performance, cycle time and ...warpage are considered. Melt temperature, injection time, packing pressure, packing time, cooling time, and cooling temperature are taken as the design variables. A multi-objective optimization of the process parameters is then performed. First, the process parameters of conformal cooling channel are optimized. Numerical simulation in the PIM is so intensive that a sequential approximate optimization using a radial basis function network is used to identify a pareto-frontier. It is found from the numerical result that the cooling performance of conformal cooling channel is much improved, compared to the conventional cooling channel. Based on the numerical result, the conformal cooling channel is developed by using additive manufacturing technology. The experiment is then carried out to examine the validity of the conformal cooling channel. Through numerical and experimental result, it is confirmed that the conformal cooling channel is effective to the short cycle time and the warpage reduction.
Based on the self‐assisted injection experimental platform, experimental studies on gas‐assisted injection molding (GAIM), and water‐assisted injection molding (WAIM) of 2 curved pipe fittings by ...adopting short‐shot method were carried out. UDF model was constructed for numerical simulation analysis. The influence rules of auxiliary medium and bending angle on the terminal morphology, inner wall surface quality at bending angle, medial and lateral residual wall thickness, variation range, and residual wall thickness deviation rate of short‐shot fluid assisted injection molding (SSFAIM) bending samples were compared. Meanwhile, the influence mechanism was investigated. The following experimental findings were obtained. SSFAIM had secondary penetration, while water produced multiple penetrations. There are multiple vacuum shrinkage pores in the unpenetrated area at the end of the SSWAIM sample, as well as serious shrinkage depressions on the surface. The shape of the penetration front of water is arc‐shaped with many penetration holes. The shape of the penetration front of the gas at the end of the SSGAIM sample is “pointy.” Compared with the SSWAIM sample, the residual wall thickness of SSGAIM has a narrow distribution range when the bending angle is 0°. With the increase of the bending angle, the “foaming” phenomenon of the inner wall surface quality at the bending angle of the SSGAIM sample becomes less and less obvious. Moreover, the deviation of the inner and outer residual wall thickness of SSGAIM is more obvious than that of SSWAIM due to the increase of bending angle.
Through the comparative analysis of the quality and residual wall thickness distribution characteristics of SSGAIM specimen and SSWAIM specimen, the influence law and mechanism would be explored, aiming to provide theoretical basis and guideline recommendations for the development of SSFAIM process.
PDF
