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Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing
Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923442/ https://www.ncbi.nlm.nih.gov/pubmed/33672464 http://dx.doi.org/10.3390/s21041467 |
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author | Shahbazi, Zeinab Byun, Yung-Cheol |
author_facet | Shahbazi, Zeinab Byun, Yung-Cheol |
author_sort | Shahbazi, Zeinab |
collection | PubMed |
description | Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach. |
format | Online Article Text |
id | pubmed-7923442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79234422021-03-03 Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing Shahbazi, Zeinab Byun, Yung-Cheol Sensors (Basel) Article Smart manufacturing systems are growing based on the various requests for predicting the reliability and quality of equipment. Many machine learning techniques are being examined to that end. Another issue which considers an important part of industry is data security and management. To overcome the problems mentioned above, we applied the integrated methods of blockchain and machine learning to secure system transactions and handle a dataset to overcome the fake dataset. To manage and analyze the collected dataset, big data techniques were used. The blockchain system was implemented in the private Hyperledger Fabric platform. Similarly, the fault diagnosis prediction aspect was evaluated based on the hybrid prediction technique. The system’s quality control was evaluated based on non-linear machine learning techniques, which modeled that complex environment and found the true positive rate of the system’s quality control approach. MDPI 2021-02-20 /pmc/articles/PMC7923442/ /pubmed/33672464 http://dx.doi.org/10.3390/s21041467 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shahbazi, Zeinab Byun, Yung-Cheol Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing |
title | Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing |
title_full | Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing |
title_fullStr | Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing |
title_full_unstemmed | Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing |
title_short | Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing |
title_sort | integration of blockchain, iot and machine learning for multistage quality control and enhancing security in smart manufacturing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923442/ https://www.ncbi.nlm.nih.gov/pubmed/33672464 http://dx.doi.org/10.3390/s21041467 |
work_keys_str_mv | AT shahbazizeinab integrationofblockchainiotandmachinelearningformultistagequalitycontrolandenhancingsecurityinsmartmanufacturing AT byunyungcheol integrationofblockchainiotandmachinelearningformultistagequalitycontrolandenhancingsecurityinsmartmanufacturing |