Study of an Online Monitoring Adaptive System for an Injection Molding Process Based on a Nozzle Pressure Curve

Abstract

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.

Optimize Injection-Molding Process Parameters and Build an Adaptive Process Control System Based on Nozzle Pressure Profile and Clamping Force

“…Therefore, by installing a pressure sensor on the injection-molding machine or the mold, the pressure sensor can monitor the pressure history of the injection-molding process and visualize the product-forming process as much as possible. In recent years, some of the literature has mentioned that installing a pressure sensor at the nozzle end can inspect the product-forming process effectively, and the pressure history of the nozzle end has a significant relationship with the product weight [ 2 , 4 , 17 , 18 , 19 , 20 ].…”

“…The nozzle peak pressure and the viscosity index are found to be highly correlated with the product weight [ 17 , 19 ]. So, in the adaptive process control system of this study, the nozzle peak pressure and the viscosity index are used as the quality indexes to monitor the variation of the part weight during the injection-molding process.…”

“…The prediction model by a neural network is incorporated into the adaptive process control system to stabilize the injection-molded product’s quality. Fan-Jiang et al [ 19 ] proved that applying a single sensor mounted on the nozzle of the injection-molding machine is sufficient to obtain accurate results. By using one sensor on the nozzle of the injection-molding machine, the cost of the adaptive process control system can be reduced, and the product weight variation can be minimized to 0.21%.…”

Intelligent Online Monitoring Technology of Green Power Transmission and Transformation Equipment Based on Internet of Things

“…In addition, in the substation environment, if the reader recognition distance can reach more than 150 m, changing the number of reader receiving antennas has no obvious effect on improving the bit error rate of the system. erefore, the performance of the system should be improved from other parameters [25].…”

Injection Barrel/Nozzle/Mold-Cavity Scientific Real-Time Sensing and Molding Quality Monitoring for Different Polymer-Material Processes

“…Scientific injection molding technologies involve the integration and collaboration of cyber-physical systems and smart manufacturing. In order to achieve adaptive process control and production optimization, the injection molding system with real-time sensing has gradually become the development and application trend of smart injection molding in the rubber and plastics industries [1][2][3][4]. Injection molding is a highly non-linear process in which many factors affect the product quality during long-run fabrication processes.…”