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Assessing Engineering Resilience for Systems with Multiple Performance Measures.

Eric Specking1, Bobby Cottam1, Gregory Parnell1

  • 1Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|September 6, 2019
PubMed
Summary

This study introduces a new framework for assessing engineered system resilience, separating it into platform and mission resilience. It uses multi-objective decision analysis to evaluate complex systems with multiple performance measures under various threats.

Keywords:
Engineering resiliencemultiple objective decision analysistransportation systems-of-systems

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Area of Science:

  • Engineering Systems Analysis
  • Resilience Engineering
  • Decision Science

Background:

  • Increasing need to model and assess system resilience against environmental and adversarial threats.
  • Existing resilience assessments often use single performance measures.
  • Resilience is studied across multiple disciplines, including engineering.

Purpose of the Study:

  • To define and utilize a resilient engineered system definition separating resilience into platform and mission resilience.
  • To propose and apply multi-objective decision analysis for assessing system resilience in systems with multiple performance measures.
  • To demonstrate methods for quantifying platform and mission resilience.

Main Methods:

  • Developed a definition separating system resilience into platform and mission resilience.
  • Applied multi-objective decision analysis with two distinct methods for quantifying resilience.
  • Illustrated methods using a transportation systems-of-systems network and a notional military example.

Main Results:

  • Quantified platform resilience by including resilience and other "ilities" in the value hierarchy.
  • Quantified mission resilience by calculating expected mission performance using "ilities" for each performance measure.
  • Demonstrated that incorporating mission resilience can improve some performance measures while negatively impacting others.

Conclusions:

  • Quantifying system resilience requires context regarding specific missions, scenarios, and threats.
  • Modeling and simulation are crucial for determining system resilience under given conditions.
  • A nuanced approach considering both platform and mission resilience is necessary for complex systems.