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Search Results (3)

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Keywords = scientific molding parameter setup

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21 pages, 12426 KiB  
Article
Scientific Molding and Adaptive Process Quality Control with External Sensors for Injection Molding Process
by Chen-Hsiang Chang, Chien-Hung Wen, Ren-Ho Tseng, Chieh-Hsun Tsai, Yu-Hao Chen, Sheng-Jye Hwang and Hsin-Shu Peng
Technologies 2025, 13(3), 97; https://doi.org/10.3390/technologies13030097 - 1 Mar 2025
Viewed by 1458
Abstract
This study established a real-time measurement system to monitor the melt quality in an injection molding process using a pressure sensor installed on the nozzle and a strain gauge installed on the tie bar. Based on the sensing curves from these two external [...] Read more.
This study established a real-time measurement system to monitor the melt quality in an injection molding process using a pressure sensor installed on the nozzle and a strain gauge installed on the tie bar. Based on the sensing curves from these two external sensors, the characteristic values of nozzle pressure and clamping force were used to optimize parameters. This study defined product weight as a quality indicator and developed a scientific molding parameter setup process. The optimization sequence of parameters is injection speed, V/P switchover point, packing pressure, packing time, and clamping force. Finally, an adaptive process control system was established based on the online quality characteristic values to maintain product quality consistency. Continuous production experiments were conducted at two sites to verify the system’s effectiveness. The results revealed that the optimized process parameters can ensure product weight stability during long-term production. Furthermore, using the adaptive process control system further enhanced product weight stability at both sites, reducing the standard deviation of product weight to 0.0289 g and 0.0148 g, and the coefficient of variation to 0.065% and 0.035%, respectively. Full article
(This article belongs to the Section Manufacturing Technology)
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27 pages, 11712 KiB  
Article
Nozzle Pressure- and Screw Position-Based CAE Scientific Process Parameter Setup for Injection Molding Process
by Ren-Ho Tseng, Chien-Hung Wen, Chen-Hsiang Chang, Yu-Hao Chen, Chieh-Hsun Tsai and Sheng-Jye Hwang
Polymers 2025, 17(2), 198; https://doi.org/10.3390/polym17020198 - 14 Jan 2025
Cited by 1 | Viewed by 947
Abstract
This study developed a scientific process parameter setup based on nozzle pressure and screw position, with the process parameter search sequence being injection speed, V/P switchover position, packing pressure, and packing time. Unlike previous studies, this study focuses on the scientific [...] Read more.
This study developed a scientific process parameter setup based on nozzle pressure and screw position, with the process parameter search sequence being injection speed, V/P switchover position, packing pressure, and packing time. Unlike previous studies, this study focuses on the scientific process parameter setup of experiments and simulations, as well as on the implementation of calibration. Experiments and simulations had the same trend of results in the scientific process parameter setup. Although the experiments and simulations had the same trend, the machine response caused parameter errors. After setting the time constant of the simulations, injection speed profiles from the experiments and simulations became closely aligned. The simulation results for the injection speed and V/P switchover position became closer to the experiment results than the results of the uncalibrated simulation. The error between the simulated and experimental injection speed was reduced from 20% to 6% after applying time constant calibration. The V/P switchover point error was also reduced from 11% to 5%, highlighting the effectiveness of the time constant to calibrate the simulation. Full article
(This article belongs to the Section Polymer Processing and Engineering)
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13 pages, 17755 KiB  
Article
Spatially Resolved, Real-Time Polarization Measurement Using Artificial Birefringent Metallic Elements
by Stefan Belle, Stefan Kefer and Ralf Hellmann
Photonics 2024, 11(5), 397; https://doi.org/10.3390/photonics11050397 - 24 Apr 2024
Viewed by 2123
Abstract
Polarization states define a fundamental property in optics. Consequently, polarization state characterization is essential in many areas of both field industrial applications and scientific research. However, a full identification of space-variant Stokes parameters faces great challenges, like multiple power measurements. In this contribution, [...] Read more.
Polarization states define a fundamental property in optics. Consequently, polarization state characterization is essential in many areas of both field industrial applications and scientific research. However, a full identification of space-variant Stokes parameters faces great challenges, like multiple power measurements. In this contribution, we present a spatially resolved polarization measurement using artificial birefringent metallic elements, the so-called hollow waveguides. Differently oriented and space-variant hollow waveguide arrays, a stationary analyzer and a CMOS camera form the basis of the experimental setup for one single spatially resolved power measurement. From this power measurement, the Stokes parameters can be calculated in quasi-real-time, with a spatial resolution down to 50 μm in square. The dimensions of the individual hollow waveguides, which are less than or equal to the employed wavelength, determine the spectral range, here in the near infrared around λ = 1550 nm. This method allows for the rapid and compact determination of spatially resolved Stokes parameters, which is experimentally confirmed using defined wave plates, as well as an undefined injection-molded polymer substrate. Full article
(This article belongs to the Special Issue Polarization Optics)
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