A reliable framework for supply chain management using cluster based blockchain for intelligent industrial automation

Industrial automation is an integral part of Industry 4.0, and this scenario needs intelligent mechanisms to improve the industry’s production level. Manufacturing industries depend entirely on supply chain management to track the entire system’s performance, which will be the key term to improving...

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Vydané v:Scientific reports Ročník 15; číslo 1; s. 22221 - 18
Hlavní autori: Alsolami, Eesa, Al-khasawenh, Mahmoud Ahmad, Alarood, Ala Abdulsalam, Alzahrani, Ahmed Omar, Ibraheem, Ahmed Aalameen, Zamani, Mazdak
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 01.07.2025
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Predmet:
639/705/1042
639/705/1046
639/705/117
639/705/258
Adversary model
Humanities and Social Sciences
Industrial automation
Intelligent manufacturing system
multidisciplinary
Probability polynomial time algorithm
Reliable supply chain management
Science
Science (multidisciplinary)
Adversary model
Intelligent manufacturing system
Reliable supply chain management
Industrial automation
Probability polynomial time algorithm
ISSN:2045-2322, 2045-2322
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Shrnutí:Industrial automation is an integral part of Industry 4.0, and this scenario needs intelligent mechanisms to improve the industry’s production level. Manufacturing industries depend entirely on supply chain management to track the entire system’s performance, which will be the key term to improving product quality. In the modern era of industrial automation, technology entirely depends on intelligent computing algorithms. This paper proposes a reliable framework for supply chain management using cluster-based blockchain technology. The proposed method contains two main contributions. The first is to maintain the information organized using Blockchain Technology, and the second is to analyze the Blockchain by extracting valuable information to make an intelligent system in industrial automation. The proposed framework’s performance evaluation is based on execution time cost analysis for Blockchain, accuracy, and mean error value analysis for the cluster-based project key factors classification. Software Development applications with 26 software metrics are used for the performance evaluation. The performance analysis for the proposed framework archives 93% for software development project clustering concerning the evaluation dataset. The result shows that the optimum average size of cluster selection will produce a high accuracy of the suitable Blockchain for the new project.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-03401-0