RESUMO
The injection-molding process is a non-linear process, and the product quality and long-term production stability are affected by several factors. To stabilize the product quality effected by these factors, this research establishes a standard process parameter setup procedure and an adaptive process control system based on the data collected by a nozzle pressure sensor and a tie-bar strain gauge to achieve this goal. In this research, process parameters such as the V/P switchover point, injection speed, packing pressure, and clamping force are sequentially optimized based on the characteristics of the pressure profile. After the optimization process, this research defines the standard quality characteristics through the optimized process parameters and combines it with the adaptive process control system in order to achieve the purpose of automatic adjustment of the machine and maintain high-quality production. Finally, three different viscosity materials are used to verify the effectiveness of the optimization procedure and the adaptive process control system. With the system, the variation of product weight was reduced to 0.106%, 0.092%, and 0.079%, respectively.
RESUMO
This research developed an adaptive control system for injection molding process. The purpose of this control system is to adaptively maintain the consistency of product quality by minimize the mass variation of injection molded parts. The adaptive control system works with the information collected through two sensors installed in the machine only-the injection nozzle pressure sensor and the temperature sensor. In this research, preliminary experiments are purposed to find master pressure curve that relates to product quality. Viscosity index, peak pressure, and timing of the peak pressure are used to characterize the pressure curve. The correlation between product quality and parameters such as switchover position and injection speed were used to produce a training data for back propagation neural network (BPNN) to compute weight and bias which are applied on the adaptive control system. By using this system, the variation of part weight is maintained to be as low as 0.14%.
RESUMO
Processing equipment and parameters will highly influence the properties of long-fiber-reinforced injection-molded thermoplastic composites, leading to different fiber lengths and orientations. Thus, maintaining fiber length during the injection molding process is always a big challenge for engineers. This study uses long-glass-fiber-reinforced polypropylene with 25 mm fiber length and a special-built novel injection molding machine with a three-barrel injection unit, including a plasticizing screw, an injection plunger, and a packing plunger, to fabricate injection molding parts while retaining long fiber length. This study also discusses the influence of process parameters, such as back pressure, screw speed, melt temperature, and different flow paths, on the properties of long-glass-fiber-reinforced composites. The experiment results show that a higher screw speed and back pressure will reduce the fiber length in the injection-molded parts. However, using appropriate parameter settings can maintain the fiber length to more than 10 mm. It was found that by increasing the back pressure, the cross direction of the fiber orientation can be increased by up to 15% and the air trap volume fraction can be decreased by up to 86%. Setting appropriate back pressure under a low screw speed will increase the tensile strength. Finally, it was found that the single-edge-gate path results in a higher tensile strength than that of the single-sprue-gate path due to the retainment of longer fiber length in the injection-molded part.
RESUMO
Injection molding is a popular process for the mass production of polymer products, but due to the characteristics of the injection process, there are many factors that will affect the product quality during the long fabrication processes. In this study, an adaptive adjustment system was developed by C++ programming to adjust the V/P switchover point and injection speed during the injection molding process in order to minimize the variation of the product weight. Based on a series of preliminary experiments, it was found that the viscosity index and peak pressure had a strong correlation with the weight of the injection-molded parts. Therefore, the viscosity index and peak pressure are used to guide the adjustment in the presented control system, and only one nozzle pressure sensor is used in the system. The results of the preliminary experiments indicate that the reduction of the packing time and setting enough clamping force can decrease the variation of the injected weight without turning on the adaptive control system; meanwhile, the master pressure curve obtained from the preliminary experiment was used as the control target of the system. With this system, the variation of the product weight and coefficient of variation (CV) of the product weight can be decreased to 0.21 and 0.05%, respectively.
