RESILIENCE ANALYSIS AND ALLOCATION FOR COMPLEX SYSTEMS USING BAYESIAN NETWORK

The concept of resilience has been explored in diverse disciplines. However, there are only a few which focus on how to quantitatively measure engineering resilience and allocate resilience in engineering system design. This paper is dedicated to exploring the gap between quantitative and qualitative assessments of engineering resilience in the domain of designing complex engineered systems, thus optimally allocating resilience into subsystems and components level in industrial applications. A conceptual framework is first proposed for modeling engineering resilience, and then Bayesian Network is employed as a quantitative tool for the assessment and analysis of engineering resilience for complex systems. One industrial based case study, a supply chain system, is employed to demonstrate the proposed approach. The proposed resilience quantification and allocation approach using Bayesian Networks would empower system designers to have a better grasp of the weakness and strength of their own systems against system disruptions induced by adverse failure events.