In this study, using Autodesk Moldflow software, the injection molding process of ventilator’, s poly (lactic acid) split filters was studied and the effective characteristics of this process were investigated and compared in two samples of crystalline and amorphous poly (lactic acid). The injection pressure for the crystalline sample showed a larger value in the simulation, which was justifiable due to the higher melt viscosity of the crystalline sample than the amorphous sample. The results of this study also showed that the cooling time required for the sample was longer, which was attributed to the difference in temperature distribution between the two samples as well as the difference in their thermal conductivity. Shrinkage and air trapping are other important characteristics in the injection process. The results showed that they were higher for the crystalline sample, which was as expected due to the difference in melt viscosity of the samples and the relationship between crystallization susceptibility and compression of polymer chains. Also, the rheological and thermal properties of selected polymers were analyzed and their relationship with effective injection factors was explained. Finally, the specifications of the injection molding machine suitable for the production of polymer filters were introduced based on the information available in the software.

Thermoplastic elastomers (TPEs) bring a combination of good plasticity of plastics and mechanical properties of elastomers that are important to component designers. These materials are especially used in the automotive industry to make a variety of parts, including strong shields. The injection process is one of the most common methods of making these polymers, which allows mass and industrial production. In this study, the injection process of elastomeric thermoplastic shield made of polypropylene / styrenebutadiene rubber + natural rubber (PP + SBR / NR) was simulated using Autodesk Moldflow software and the appropriate injection port location, optimal process conditions and possible injection defects Were discussed. Injection mold filling time, injection pressure, melt and mold temperature, cooling time, warpage and shrinkage are among the parameters that have been analyzed in this study. Also, possible positions of air trapping and weld lines were identified as the most common possible injection defects.

Injection molding is the most widely used process for producing plastic parts.In this process, an important issue is to predict and optimize the warpage before manufacturing. In this paper, a simulation with MOLDFLOW software is proposed to optimize the injection molding process. The optimization process aims at minimizing the warpage of the critical injection molding part in which process parameters, gate location and its shape are the design variables. Moldflow Plastic Insight software is used to analyze the warpage of the injection molding part. The mold temperature, melt temperature, injection time, packing pressure and packing time are regarded as process parameters. The results shown that to reduce warpage in plastc part not only the process parameters should be optimized but also effect of gate shape and especially its position should be considered in precise parts. Moreover the results shown that moldflow injection molding simulation software is able to accurately predict the part warpage, but it doesn’t consider the viscoelastic behaviour of plastic material in process.

In the process of molding parts using the plastic injection molding method, it is key essential to apply appropriate parameters in order to produce a qualified product. The purpose of this paper is to choose helpful production parameters and optimize them for molding eight different parts made from Polyetherimide. In the beginning, based on the previous research and the capabilities of Mold Flow software, appropriate process parameters were chosen. These parameters were: melt temperature, mold surface temperature, packing pressure and coolant inlet temperature. The simulations in Mold Flow software were done based on Taguchi’s L25 orthogonal array. Afterward, the critical and comparable results including: volumetric shrinkage, sink mark, warpage and the percentage of frozen volume in parts were exported from the simulations. Eventually, the optimizations were made based on these results by applying the gray relational analysis. The optimizing results show that in all distinguishing coefficients of the gray relational analysis (0.1 to 0.9), the melt temperature was 360 °c, the mold surface temperature was 140 °c, the packing pressure was 100% of the injection pressure and the coolant inlet temperature was 12.5 °c lower than the mold surface temperature of the most optimized ones. Also based on the ANOVA results, in all difference indices, parameters of melt temperature and packing pressure were respectively the most effective.

Product quality for plastic injection molding process is highly related with the settings for its process parameters. Additionally, the product quality is not simply based on a single quality index, but multiple interrelated quality indices. To find the settings for the process parameters such that the multiple quality indices can be simultaneously optimized is becoming a research issue and is now known as finding the efficient frontier of the process parameters. This study considers three quality indices in the plastic injection molding: war page, shrinkage, and volumetric shrinkage at ejection. A digital camera thin cover is taken as an investigation example to show the method of finding the efficient frontier. Solidworks and Moldflow are utilized to create the part’s geometry and to simulate the injection molding process, respectively. Nine process parameters are considered in this research: injection time, injection pressure, packing time, packing pressure, cooling time, cooling temperature, mold open time, melt temperature, and mold temperature. Taguchi's orthogonal array L27 is applied to run the experiments, and analysis of variance is then used to find the significant process factors with the significant level 0.05. In the example case, four process factors are found significant. The four significant factors are further used to generate 34 experiments by complete experimental design. Each of the experiments is run in Moldflow. The collected experimental data with three quality indices and four process factors are further used to generate three multiple regression equations for the three quality indices, respectively. Then, the three multiple regression equations are applied to generate 1,225 theoretical datasets. Finally, data envelopment analysis is adopted to find the efficient frontier of the 1,225 theoretical datasets. The found datasets on the efficient frontier are with the optimal quality. The process parameters of the efficient frontier are further validated by Moldflow. This study demonstrates that the developed procedure has proved a useful optimization procedure that can be applied in practice to the injection molding process.

Injection molding process is one of the most important methods of forming in the plastics manufacturing industry. Shrinkage and out of roundness are phenomenons that affect the final product quality. In this study, the effect of the thickness of cylindrical parts from polypropylene material on shrinkage and out of roundness has been investigated. For this purpose, injection molding process is simulated and analyzed with MOLDFLOW software. Then a five-cavity injection mold from hallow cylindrical parts with five different thicknesses is made. Using an injection molding machine least five samples of these parts are made. Then dimensions of samples are measured using 3D optical coordinate measuring machine and the amount of shrinkage of each sample is obtained. It can be concluded that with increasing part thickness, shrinkage and out of roundness are increased. It is because of being slower at melting material cools and having more time to make crystals. More crystallize caused to more shrinkage and more out of roundness. At the end, the simulation results are compared with the experimental results and showed a good agreement.

Extrusion, injection molding, calendaring, and thermoforming are just a few of the processing techniques utilized in the plastics industry. Gas-assist injection molding plays a crucial role in this equipment. The advancement of standard injection molding is represented by this apparatus. Parts with thin wall thickness and hollow sections can be manufactured using this method. Use this strategy to save between 30% and 35% of the material. In this procedure, gas is first introduced after a brief shot of material is injected. The remaining portion of the cavity is filled in by injecting gas. The hollow section is described in detail by the gas core. In gas-assist injection molding, the geometry of the gas channel design is also very important. There is a wide variety of materials available for polymeric applications. Different polyamide materials, including polypropylene, polycarbonate, high-impact polystyrene, and polyethylene terephthalate (PET), can be processed using gas-assisted injection molding. Talc-filled polypropylene has been chosen for this study's simulation and experimental work. For simulation purposes, Moldflow plastic insight is utilized. Moldflow plastic insight was used to simulate the tensile samples, and gas-assist injection molding was used to create the experimental models. Simulation and experimental results are used to measure the wall thickness and gas penetration depth. The validation was then checked by comparing these results.

In the plastic industry, distinctive handling hardware like expulsion, infusion trim, Calendaring, and thermoforming are utilized to fabricate various products. This equipment is fundamentally the improvement of Standard Injection Molding which Injection Molding is significant. This procedure is utilized for the assembling of the hollow section part and the part with thin wall thickness. This research aimed to develop a halogen-based Headlamp for a two-wheeler vehicle. The essential objective of an automotive headlight is to enhance safety and protection in low light and poor climate conditions. It is the first time that a halogen-based headlamp for a two-wheeler vehicle has been created for the first time in Pakistan. The product in our project consists of three major components, reflector, halogen bulb, and lens. Material selection and processing were the two major tasks in this project. The product was manufactured through injection molding, a high vacuum metallization process, and then finally assembling of parts. To determine the quality of the product, six tests were performed according to the Japanese standard JIS-D5500.

The main objective of this paper is to predict 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 for 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 pressure and the mold temperature on warpage were numerically analyzed. In the second step, a group of data that had been obtained from analysis results was 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.

Injection molding is one of the common processes for producing plastic parts. In this process, the mold is filled immediately and then the part and mold will be cooled down during the packing time. In the end, the part will be ejected from the mold. In this study, the effects of the most important processing parameters such as packing time, melt and mold temperature have been investigated on shrinkage and warpage of the products experimentally and numerically. According to previous reports, a thin sheet is defined by a length to thickness ratio of at least 100. MOLDFLOW software has been utilized to obtain the numerical results. For the empirical study, 64 specimens have been produced in different production conditions. These samples have been scanned by a 3D scanner and results have been analyzed by CATIA software. The findings show that increasing melt and mold temperature decreases the warpage amount and rises the shrinkage in the specimens. Also increasing the packing time up to 2 seconds increases the warpage and decreases the shrinkage noticeably but in longer packing times the variations will be less remarkable. Moreover, findings show that the general trend in simulated and experimental results are similar in all reported values of shrinkage and warpage, in which the maximum calculated errors for both of them are approximately 10%.