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Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation

Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for th...

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Detalles Bibliográficos
Autores principales: Zheng, Xin, Zhang, Xiaodong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857848/
https://www.ncbi.nlm.nih.gov/pubmed/36673186
http://dx.doi.org/10.3390/e25010045
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author Zheng, Xin
Zhang, Xiaodong
author_facet Zheng, Xin
Zhang, Xiaodong
author_sort Zheng, Xin
collection PubMed
description Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for the two models, and three different robustness attack strategies are proposed. To verify the effectiveness of the proposed method, a case study is then conducted on a cloud manufacturing project of a new energy vehicle. The results show that both the structural and process-based robustness of the system are lowest under the betweenness-based failure mode, indicating that resource nodes with large betweenness are most important to the robustness of the project. Therefore, the cloud manufacturing platform should focus on monitoring and managing these resources so that they can provide stable services. Under the individual server failure mode, system robustness varies greatly depending on the failure behavior of the service provider: Among the five service providers (S1–S5) given in the experimental group, the failure of Server 1 leads to a sharp decline in robustness, while the failure of Server 2 has little impact. This indicates that the CMS can protect its robustness by identifying key servers and strengthening its supervision of them to prevent them from exiting the platform.
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spelling pubmed-98578482023-01-21 Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation Zheng, Xin Zhang, Xiaodong Entropy (Basel) Article Cloud manufacturing systems (CMSs) are networked, distributed and loosely coupled, so they face great uncertainty and risk. This paper combines the complex network model with multi-agent simulation in a novel approach to the robustness analysis of CMSs. Different evaluation metrics are chosen for the two models, and three different robustness attack strategies are proposed. To verify the effectiveness of the proposed method, a case study is then conducted on a cloud manufacturing project of a new energy vehicle. The results show that both the structural and process-based robustness of the system are lowest under the betweenness-based failure mode, indicating that resource nodes with large betweenness are most important to the robustness of the project. Therefore, the cloud manufacturing platform should focus on monitoring and managing these resources so that they can provide stable services. Under the individual server failure mode, system robustness varies greatly depending on the failure behavior of the service provider: Among the five service providers (S1–S5) given in the experimental group, the failure of Server 1 leads to a sharp decline in robustness, while the failure of Server 2 has little impact. This indicates that the CMS can protect its robustness by identifying key servers and strengthening its supervision of them to prevent them from exiting the platform. MDPI 2022-12-27 /pmc/articles/PMC9857848/ /pubmed/36673186 http://dx.doi.org/10.3390/e25010045 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
Zheng, Xin
Zhang, Xiaodong
Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
title Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
title_full Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
title_fullStr Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
title_full_unstemmed Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
title_short Robustness of Cloud Manufacturing System Based on Complex Network and Multi-Agent Simulation
title_sort robustness of cloud manufacturing system based on complex network and multi-agent simulation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857848/
https://www.ncbi.nlm.nih.gov/pubmed/36673186
http://dx.doi.org/10.3390/e25010045
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