Cascading failure resilience analysis and recovery of automotive manufacturing supply chain networks considering enterprise roles

Abstract

With the rapid development of global trade, the member enterprises in the automotive manufacturing supply chain are widely spread around the world. As a result, the scale of the automotive manufacturing supply chain network has become increasingly large, and the structure has become more complex. At the same time, the connection between enterprises is becoming closer. On one hand, the close business relationships between enterprises and the vast network structure accelerate the operation efficiency of the automotive manufacturing supply chain network. On the other hand, it also exposes the entire network system to high risks of cascading failures when facing disruptions due to enterprise production interruptions. Therefore, this work aims to establish a realistic cascading failure model for the automotive manufacturing supply chain network to explore its cascading failure characteristics. Based on this model, a two-stage recovery strategy is proposed to enhance the network’s cascading failure resilience. Experimental results demonstrate the following findings: (1) underload nodes that emerge after load redistribution are the main cause of cascading failure resilience degradation in automotive manufacturing supply chain networks; (2) cascading failure resilience is negatively correlated with the load-exponential coefficient, the capacity lower-limit coefficient, and the attenuation-tolerance coefficient; (3) among four different types of attacks, cascading failures caused by the high eigenvector centrality attack strategy and the high degree attack strategy impose the most severe damage on the automotive manufacturing supply chain network; (4) the proposed two-stage recovery strategy can significantly improve the cascading failure resilience of the automotive manufacturing supply chain network.