Developing a Quantitative Resiliency Approach

TL;DR

This paper explores the foundations of resiliency engineering and proposes a quantitative approach to resiliency-informed decision-making for critical infrastructure systems, emphasizing response to failure over failure avoidance.

Contribution

It introduces a novel framework for quantifying resiliency, bridging the gap between qualitative understanding and quantitative decision-making in complex systems.

Findings

Resiliency can be quantitatively defined and measured.

The proposed approach enhances decision-making in critical infrastructure.

Resiliency-focused metrics improve system robustness understanding.

Abstract

Resiliency has garnered attention in the management of critical infrastructure as a metric of system performance, but there are significant roadblocks to its implementation in a realistic decision-making framework. Contrasted to risk and reliability, which have robust quantification approaches and undergird many regulatory approaches to system safety (e.g., "risk-informed decision-making"), resiliency is a diffuse, qualitatively-understood characteristic, often treated differently or distinctly. However, in the emerging context of highly-complex, highly-interdependent critical systems, the idea of reliability (as the probability of non-failure) may not be an appropriate metric of system health. As a result, focus is shifting towards resiliency-centered approaches that value the response to failure as much as the avoidance of failure. Supporting this approach requires a robustly-defined, quantitative understanding of resiliency. In this paper, we explore the foundations of reliability and resiliency engineering, and propose an approach to resiliency-informed decision-making bolstered by a quantitative understanding of resiliency.