Feasibility assessment of injection molding online monitoring based on oil pressure/nozzle pressure/cavity pressure-Reference-Cited by-同舟云学术

Feasibility assessment of injection molding online monitoring based on oil pressure/nozzle pressure/cavity pressure

Published:2023-02-22 Issue:3 Volume:38 Page:375-386
ISSN:0930-777X
Container-title:International Polymer Processing
language:en
Short-container-title:

Author:

Tsou Hao-Hsuan¹^ORCID,Huang Chung-Ching¹,Wang Zhi-Hao²,Zhao Ting-Wei¹

Affiliation:

1. Department of Mold and Die Engineering , National Kaohsiung University of Science and Technology , No. 415, Chien-Kung Road , Kaohsiung City 807 , Taiwan ROC

2. Department of Information Management , Southern Taiwan University of Science and Technology , No. 1, Nantai St, Yongkang Dist , Tainan City 710301 , Taiwan ROC

Abstract

Abstract This study produced a box-like product through injection molding, and pressure sensors were installed at the nozzle in the injection molding machine and mold cavity. Injection molding experiments were conducted with various process parameters to understand the correlations between the pressure of the cavity, nozzle, and oil pump. A high correlation (R > 0.95) between oil pressure and nozzle pressure could be found in the study. The oil pressure in the injection molding machine could fully describe the pressure variation of the molten plastic at the nozzle. However, the correlation between nozzle pressure and cavity pressure was slightly reduced due to changes in injection speed, melting temperature, and packing time. Thus, a suitable molding window can improve the correlation between oil pressure, nozzle pressure, and cavity pressure. This study provides a correlation between the three pressures and a reference for the future selection of process variables, an essential pretreatment for online monitoring.

Funder

National Science and Technology Council, Taiwan

Publisher

Walter de Gruyter GmbH

Subject

Materials Chemistry,Industrial and Manufacturing Engineering,Polymers and Plastics,General Chemical Engineering

Link

https://www.degruyter.com/document/doi/10.1515/ipp-2022-4281/pdf

Reference16 articles.

1. Ageyeva, T., Horváth, S., and Kovács, J.G. (2019). In-mold sensors for injection molding: on the way to Industry 4.0. Sensors 19: 3551, https://doi.org/10.3390/s19163551.

2. Chen, J.-Y., Yang, K.-J., and Huang, M.-S. (2018). Online quality monitoring of molten resin in injection molding. Int. J. Heat Mass Transfer 122: 681–693, https://doi.org/10.1016/j.ijheatmasstransfer.2018.02.019.

3. Chen, Y.-S., Wu, K.-T., Tsai, M.-H., Hwang, S.-J., Lee, H.-H., Peng, H.-S., and Chu, H.-Y. (2019). Adaptive process control of the changeover point for injection molding process. J. Low Freq. Noise Vib. Act. Control 40: 383–394, https://doi.org/10.1177/1461348419875057.

4. Fan-Jiang, J.-C., Su, C.-W., Liou, G.-Y., Hwang, S.-J., Lee, H.-H., Peng, H.-S., and Chu, H.-Y. (2021). Study of an online monitoring adaptive system for an injection molding process based on a nozzle pressure curve. Polymers 13: 555, https://doi.org/10.3390/polym13040555.

5. Farooque, R., Asjad, M., and Rizvi, S.J.A. (2021). A current state of art applied to injection moulding manufacturing process – a review. Mater. Today Proc. 43: 441–446, https://doi.org/10.1016/j.matpr.2020.11.967.

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