Measuring and Architecting System Resilience Through Trade Study Analysis

Resilience is a dimension of trade study analysis that must be accounted for in early conceptual system design because it can influence cost, reliability, performance, and overall lifecycle cost. Traditional trade studies, which focus on risk, safety, and costs aspects analysis are no longer sufficient because they only account for predicted and known disruptions. This article proposes a practical and implementable methodology for measuring, predicting, and architecting system resilience during conceptual design that considers both known and unknown disruptions. This article extends the current literature by motivating the resilience curve using a Markov process, verifying resilience with empirical data, and incorporating the interaction between subsystems using common cause failure with the binomial failure rate. A verified simulation model is used as a predictive analysis tool and applied to an unmanned surface vehicle case study.