Research on Quality Control of Intelligent Injection Molding System Based on Process Monitoring

In order to reduce the injection cost of large-scale manufacturing industry and solve the problem of uncontrollable quality in the production process, this paper studies the quality control of an intelligent injection molding system based on process monitoring. The system can reliably and objectively monitor the changes of cavity pressure and temperature at different positions in the mold forming process. When the product quality is abnormal, the cavity pressure curve will change greatly. Through the system, the abnormal products can be automatically screened out, the automation of quality detection can be realized, and the qualified rate of quality products can be improved. Based on the data of cavity pressure and temperature collected by the system, a BP neural network pressure prediction model is established. The model takes some important process parameters, the pressure value at the beginning of filling as the input, and the cavity pressure at the remaining stages as the output. Through the model, the expected prediction accuracy is obtained. Finally, it can be implemented on the injection molding machine, and the injection molding process can be adjusted online Some input values in the process provide data support for further quality control.