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Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology

The development of Information Technology has intruded the chemical industry. In the conventional chemical industry, humans are involved in monitoring the chemical evaporation processes. If there is any damage, then humans suffer enormously. These drawbacks are overcome in the chemical industry by i...

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Detalles Bibliográficos
Autores principales: Zhang, Haifeng, Zhou, Lianzhu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417760/
https://www.ncbi.nlm.nih.gov/pubmed/36035852
http://dx.doi.org/10.1155/2022/3811320
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author Zhang, Haifeng
Zhou, Lianzhu
author_facet Zhang, Haifeng
Zhou, Lianzhu
author_sort Zhang, Haifeng
collection PubMed
description The development of Information Technology has intruded the chemical industry. In the conventional chemical industry, humans are involved in monitoring the chemical evaporation processes. If there is any damage, then humans suffer enormously. These drawbacks are overcome in the chemical industry by implanting the sensors to the required blocks for monitoring the levels of chemical substances. An alert system can be introduced with an artificial intelligence algorithm to regenerate the process using details updated in the database. In this research, the machine-based Time-Temperature Superposition (TTS) method is implemented to monitor the chemical reactions in the chemical component manufacturing company.
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spelling pubmed-94177602022-08-27 Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology Zhang, Haifeng Zhou, Lianzhu Comput Intell Neurosci Research Article The development of Information Technology has intruded the chemical industry. In the conventional chemical industry, humans are involved in monitoring the chemical evaporation processes. If there is any damage, then humans suffer enormously. These drawbacks are overcome in the chemical industry by implanting the sensors to the required blocks for monitoring the levels of chemical substances. An alert system can be introduced with an artificial intelligence algorithm to regenerate the process using details updated in the database. In this research, the machine-based Time-Temperature Superposition (TTS) method is implemented to monitor the chemical reactions in the chemical component manufacturing company. Hindawi 2022-08-19 /pmc/articles/PMC9417760/ /pubmed/36035852 http://dx.doi.org/10.1155/2022/3811320 Text en Copyright © 2022 Haifeng Zhang and Lianzhu Zhou. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Haifeng
Zhou, Lianzhu
Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology
title Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology
title_full Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology
title_fullStr Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology
title_full_unstemmed Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology
title_short Study on Regenerative Processing Performance of Chlorinated Polyethylene Based on Wireless Network and Artificial Intelligence Technology
title_sort study on regenerative processing performance of chlorinated polyethylene based on wireless network and artificial intelligence technology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9417760/
https://www.ncbi.nlm.nih.gov/pubmed/36035852
http://dx.doi.org/10.1155/2022/3811320
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