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Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation

In the process of injection molding, a certain percentage of recycled material is usually used in order to save costs. The material properties of recycled materials can change significantly compared with raw materials, and the quality of their molded products is more difficult to control. Therefore,...

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Detalles Bibliográficos
Autores principales: Chang, Hanjui, Su, Zhiming, Lu, Shuzhou, Zhang, Guangyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877480/
https://www.ncbi.nlm.nih.gov/pubmed/35215590
http://dx.doi.org/10.3390/polym14040679
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author Chang, Hanjui
Su, Zhiming
Lu, Shuzhou
Zhang, Guangyi
author_facet Chang, Hanjui
Su, Zhiming
Lu, Shuzhou
Zhang, Guangyi
author_sort Chang, Hanjui
collection PubMed
description In the process of injection molding, a certain percentage of recycled material is usually used in order to save costs. The material properties of recycled materials can change significantly compared with raw materials, and the quality of their molded products is more difficult to control. Therefore, it is crucial to propose a method that can effectively maintain the yield of the recycled material products. In addition, the variation of clamping force during the injection molding process can be determined by measuring the tie-bar elongation of the injection molding machine. Therefore, this study proposes a real-time product quality monitoring system based on the variation of clamping force during the injection molding process for the injection molding of recycled materials for plastic bottle caps. The variation of clamping force reflects the variation of cavity pressure during the injection molding process and further maps the variation of injection parameters during the injection molding process. Therefore, this study evaluates the reliability of the proposed method for three different injection parameters (residual position, metering end point and metering time). Experiments have shown that there is a strong correlation between the quality (geometric properties) and weight of the product under different molding parameters. Moreover, the three main injection parameters have a strong influence on the weight and quality of the plastic caps. The variation of the clamping force is also highly correlated with the weight of the plastic bottle cap. This demonstrates the feasibility of applying the variation of clamping force to monitor the quality of injection molded products. Furthermore, by integrating the clamping force variation index with the calibration model of the corresponding injection parameters, it is possible to control the weight of the plastic cap within the acceptable range of the product in successive production runs.
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spelling pubmed-88774802022-02-26 Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation Chang, Hanjui Su, Zhiming Lu, Shuzhou Zhang, Guangyi Polymers (Basel) Article In the process of injection molding, a certain percentage of recycled material is usually used in order to save costs. The material properties of recycled materials can change significantly compared with raw materials, and the quality of their molded products is more difficult to control. Therefore, it is crucial to propose a method that can effectively maintain the yield of the recycled material products. In addition, the variation of clamping force during the injection molding process can be determined by measuring the tie-bar elongation of the injection molding machine. Therefore, this study proposes a real-time product quality monitoring system based on the variation of clamping force during the injection molding process for the injection molding of recycled materials for plastic bottle caps. The variation of clamping force reflects the variation of cavity pressure during the injection molding process and further maps the variation of injection parameters during the injection molding process. Therefore, this study evaluates the reliability of the proposed method for three different injection parameters (residual position, metering end point and metering time). Experiments have shown that there is a strong correlation between the quality (geometric properties) and weight of the product under different molding parameters. Moreover, the three main injection parameters have a strong influence on the weight and quality of the plastic caps. The variation of the clamping force is also highly correlated with the weight of the plastic bottle cap. This demonstrates the feasibility of applying the variation of clamping force to monitor the quality of injection molded products. Furthermore, by integrating the clamping force variation index with the calibration model of the corresponding injection parameters, it is possible to control the weight of the plastic cap within the acceptable range of the product in successive production runs. MDPI 2022-02-10 /pmc/articles/PMC8877480/ /pubmed/35215590 http://dx.doi.org/10.3390/polym14040679 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chang, Hanjui
Su, Zhiming
Lu, Shuzhou
Zhang, Guangyi
Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation
title Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation
title_full Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation
title_fullStr Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation
title_full_unstemmed Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation
title_short Intelligent Predicting of Product Quality of Injection Molding Recycled Materials Based on Tie-Bar Elongation
title_sort intelligent predicting of product quality of injection molding recycled materials based on tie-bar elongation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877480/
https://www.ncbi.nlm.nih.gov/pubmed/35215590
http://dx.doi.org/10.3390/polym14040679
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AT zhangguangyi intelligentpredictingofproductqualityofinjectionmoldingrecycledmaterialsbasedontiebarelongation