A Novel Methodology for Online Quality Monitoring during Injection Molding

• Main Authors: Tseng, Chien-Chou, 曾健洲
• Other Authors: Huang, Ming-Shyan
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/725bdx

碩士 === 國立高雄第一科技大學 === 機械與自動化工程系碩士班 === 106 === Traditionally, molded part quality is difficult to predict during injection molding process. Recently, sensing technology was well refined. For the purpose of intelligent injection molding process, the process information can be collected through the sensors installed on the equipment and injection tool. The correlation between injection quality and process information can be understood by applying statistical methods. In this research, the monitoring methodology of injection molded part quality in the injection molding process, which is based on the characteristic of measured clamping force curve on the tie bar of injection molding machine, was developed. The effect of melt quality on injection molded part was investigated by comparing the characteristics on measuring curves, which were detected on tie bar, injection unit, nozzle, sprue and cavity of injection tool. The quality index of injection molded part was designed based on the characteristic of clamping force curve, and was verified by pressure peak, viscosity and energy indexes, which are related with melt quality. By varying plasticization parameters including barrel temperature, back pressure, and screw rotational speed, the purpose was to observe the effect of melt quality on injection molded part by fluctuating melt quality, and the accuracy of the methodology revealed in this research was also discussed through melt quality indexes. In experimental results, there was a strong correlation between clamping force increment and molded part quality. Accordingly, it was effective to online monitor injection molded part quality. Moreover, melt quality indexes captured from system pressure and nozzle pressure at the initial melt filling stage were effectively responded to the influence of melt quality on molded part. Comparably, those captured from cavity pressure in the final melt filling stage were closed to molded part quality. Anyhow, the coincidence between melt quality indexes and clamping force increment were all accurately predicted the injection molded part quality. Considering the installation convenience and industrial practicability, the application of tie bar strain sensor was not only to monitor the variation of clamping force but also effectively predict injection molded part quality.