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

Area of Science:

• Manufacturing Systems Engineering
• Complex Network Theory
• Simulation Modeling

Background:

• Cloud manufacturing systems (CMSs) are inherently complex, distributed, and loosely coupled, leading to significant uncertainty and risk.
• Assessing the robustness of these systems is crucial for ensuring reliable operations and service delivery.

Purpose of the Study:

• To develop and validate a novel approach for analyzing the robustness of cloud manufacturing systems.
• To identify critical components and failure modes that impact system robustness.

Main Methods:

• Integration of complex network models with multi-agent simulation for robustness analysis.
• Proposal and application of three distinct robustness attack strategies.
• Evaluation using diverse metrics tailored to network and simulation models.

Main Results:

• The betweenness-based failure mode significantly reduces both structural and process-based robustness, highlighting the importance of high-betweenness resource nodes.
• System robustness is highly sensitive to individual server failures; Server 1's failure drastically impacts robustness, while Server 2's failure has minimal effect.

Conclusions:

• Cloud manufacturing platforms must prioritize monitoring and management of critical resource nodes (identified by high betweenness) to ensure stable services.
• Identifying and strengthening supervision of key servers is essential for protecting CMS robustness against individual service provider failures.