The Structure of Vulnerable Nodes in Behavioral Network Models of Complex Engineered Systems

All methods associated with failure analysis attempt to identify critical design variables and parameters such that appropriate process controls can be implemented to detect problems before they occur. This paper introduces a new approach to the identification of critical design variables and parameters through the concept of bridging nodes. Using a network-based perspective in which design parameters and variables are modeled as nodes, results show that vulnerable parameters tend to be bridging nodes, which are nodes that connect two or more groups of nodes that are organized together in order to perform an intended function. This paper extends existing modeling capabilities based upon a behavioral network analysis (BNA) approach and presents empirical results identifying the relationship between bridging nodes and parameter vulnerability as determined by existing, network metric-based methods. These topological network robustness metrics were used to analyze a large number of engineering systems. Bridging nodes are associated with significantly larger changes in network degradation, as measured by these metrics, than non-bridging nodes when subject to attack (p < 0.001). The results indicate the structural role of vulnerable design parameters in a behavioral network.