Assessing Engineering Resilience for Systems with Multiple Performance Measures. Issue 9 (5th September 2019)

• Record Type: Journal Article
• Authors: Specking, Eric; Cottam, Bobby; Parnell, Gregory; Pohl, Edward; Cilli, Matthew; Buchanan, Randy; Wade, Zephan; Small, Colin
• Is Part Of: Risk analysis. Volume 39:Issue 9(2019)
• Page Start: 1899
• Page End: 1912
• Publication Date: 2019-09-05
• Subjects: Engineering resilience -- multiple objective decision analysis -- transportation systems‐of‐systems; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.13395
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract: Recently, efforts to model and assess a system's resilience to disruptions due to environmental and adversarial threats have increased substantially. Researchers have investigated resilience in many disciplines, including sociology, psychology, computer networks, and engineering systems, to name a few. When assessing engineering system resilience, the resilience assessment typically considers a single performance measure, a disruption, a loss of performance, the time required to recover, or a combination of these elements. We define and use a resilient engineered system definition that separates system resilience into platform and mission resilience. Most complex systems have multiple performance measures; this research proposes using multiple objective decision analysis to assess system resilience for systems with multiple performance measures using two distinct methods. The first method quantifies platform resilience and includes resilience and other "ilities" directly in the value hierarchy, while the second method quantifies mission resilience and uses the "ilities" in the calculation of the expected mission performance for every performance measure in the value hierarchy. We illustrate the mission resilience method using a transportation systems‐of‐systems network with varying levels of resilience due to the level of connectivity and autonomy of the vehicles and platform resilience by using a notional military example. Our analysis found that it is necessary to quantify performance in context with specific mission(s) and scenario(s) under specific threat(s) and then use modeling and simulation to help determine the resilience of a system for a given set of conditions. The example demonstrates how incorporating system mission resilience can improve performance for some performance measures while negatively affecting others.