Quality Indexes Design for Online Monitoring Polymer Injection Molding

Chen, Jianyu; Tseng, Chien-Chou; Huang, Ming‐Shyan

doi:10.1155/2019/3720127

Cited by 35 publications

(23 citation statements)

References 34 publications

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“…Cavity pressure has been found to be a reliable process indicator in injection molding, for both part quality and process monitoring [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. Specifically, it has been found to provide real-time detection of part and process deviation.…”

Section: Introductionmentioning

confidence: 99%

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

et al. 2021

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The cavity pressure in the injection molding process is closely related to the quality of the molded products, and is used for process monitoring and control, to upgrade the quality of the molded products. The experimental platform was built to carry out the cavity pressure experiment with a micro spline injection mold in the paper. The process parameters were changed, such as V/P switchover, mold temperature, melt temperature, packing pressure, and injection rate, in order to analyze the influence of the process parameters on the product weight. The peak cavity pressure and area under the pressure curve were the two attributes utilized in investigating the correlation between cavity pressure and part weight. The experimental results show that the later switchover allowed the injection to proceed longer and produce a heavier tensile specimen. By comparing different cavity pressure curves, the general shapes of the curves were able to indicate different types of shortage produced. When the V/P switchover position is 10 mm, the coefficient of determination (R2 value) of part weight, for the peak cavity pressure and area under the curve, were 0.7706 and 0.8565, respectively. This showed that the area under the curve appeared to be a better process and quality indicator than the peak cavity pressure.

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Section: Introductionmentioning

confidence: 99%

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

et al. 2021

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“…This index is related to the overall pressure characteristics of the polymer melt during the injection molding process. Deviations may reflect changes in part quality, particularly weight changes [ 30 ].

…”

Section: Methodsmentioning

confidence: 99%

Quality Prediction for Injection Molding by Using a Multilayer Perceptron Neural Network

Ke¹,

Huang²

2020

Polymers

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Injection molding has been widely used in the mass production of high-precision products. The finished products obtained through injection molding must have a high quality. Machine parameters do not accurately reflect the molding conditions of the polymer melt; thus, the use of machine parameters leads to erroneous quality judgments. Moreover, the cost of mass inspections of finished products has led to strict restrictions on comprehensive quality testing. Therefore, an automatic quality inspection that provides effective and accurate quality judgment for each injection-molded part is required. This study proposes a multilayer perceptron (MLP) neural network model combined with quality indices for performing fast and automatic prediction of the geometry of finished products. The pressure curves detected by the in-mold pressure sensor, which reflect the flow state of the melt, changes in various indicators and molding quality, were considered in this study. Furthermore, the quality indices extracted from pressure curves with a strong correlation with the part quality were input into the MLP model for learning and prediction. The results indicate that the training and testing of the first-stage holding pressure index, pressure integral index, residual pressure drop index and peak pressure index with respect to the geometric widths were accurate (accuracy rate exceeded 92%), which demonstrates the feasibility of the proposed method.

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“…Chen et al [15,16] investigated the effect of mold separation on molded part quality through a precise linear displacement transducer installed outside the mold plates, and found that the maximum mold separation occurring in the V/P switchover is highly correlated with part weight. Chen et al [17] conducted an experimental verification of several quality indexes, including peak pressure, viscosity extracted pressure profiles from the system, the nozzle, and the cavity, as well as the clamping force increment extracted from the tie-bar elongation profile. They found that these quality indexes, especially the clamping force increment index, have a strong correlation with the part quality.…”

Section: Literature Reviewmentioning

confidence: 99%

Tie-Bar Elongation Based Filling-To-Packing Switchover Control and Prediction of Injection Molding Quality

Chen

Liu²,

Huang³

2019

Polymers

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Filling-to-packing switchover (also called V/P switchover) is critical for assuring injection molding quality. An improper V/P switchover setting may result in various defects of injection-molded parts, such as excessive residual stress, flash, short shot, and warpage, etc. To enhance a consistent molding quality, recent V/P switchover approaches adopt cavity pressure profiles requiring sensors embedded in mold cavities, which is invasive to mold cavities and more expensive. Instead of using cavity pressure sensors, by working with the most popular screw position switchover control, this study hereby proposes a novel approach of tuning V/P switchover timing using a tie-bar elongation profile. In this investigation, a dumbbell testing specimen mold is applied to verify the feasibility of the method proposed. The results show that the mold filling and packing stages can be observed along the tie-bar elongation profile, detected by mounting strain gauges on the tie bars. Also, the characteristics of the cavity pressure are similar to those of the tie-bar elongation profile under a proper clamping force condition. Moreover, the varying process parameter settings which include injection speed, V/P switchover point, and holding pressure, can be reflected in these profiles. By extracting their characteristics, the application of the V/P switchover is proved to be realistic. This research conducted an experiment to verify the proposed V/P switchover decision method based on the tie-bar elongation profile. The result showed that the fluctuation of the part’s weight corresponding to a slight change of the barrel’s temperature from 210 °C to 215 °C can be successfully controlled with this method. Besides, the maximum clamping force increment extracted from the tie-bar elongation profile was found to be a good indicator for online monitoring of the reground material variation.

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Quality Indexes Design for Online Monitoring Polymer Injection Molding

Cited by 35 publications

References 34 publications

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

Research on Quality Characterization Method of Micro-Injection Products Based on Cavity Pressure

Quality Prediction for Injection Molding by Using a Multilayer Perceptron Neural Network

Tie-Bar Elongation Based Filling-To-Packing Switchover Control and Prediction of Injection Molding Quality

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