3.1.2 Exploring Resilience Measurement Methodologies

Erol, Ozgur; Henry, Devanandham; Sauser, Brian

doi:10.1002/j.2334-5837.2010.tb01072.x

Cited by 13 publications

(16 citation statements)

References 35 publications

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“…Since 2002, efforts to model and assess a system's resilience to disruptions due to environmental and adversarial threats have increased substantially. The desire to define and assess engineering system resilience is highlighted in the literature (Erol, Henry, & Sauser, ; Hosseini, Barker, & Ramirez‐Marquez, ; Larkin et al., ; Reid & Botterill, ; Ryan, Jacques, & Colombi, ).…”

Section: Introductionmentioning

confidence: 99%

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Assessing Engineering Resilience for Systems with Multiple Performance Measures

et al. 2019

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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.

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Section: Introductionmentioning

confidence: 99%

“…Several authors present different definitions for resilience (Erol et al., ; Hosseini et al., ; Larkin et al., ; Reid & Botterill, ; Ryan et al., ). For example, Larkin et al.…”

Section: Introductionmentioning

confidence: 99%

Assessing Engineering Resilience for Systems with Multiple Performance Measures

et al. 2019

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“…Labels included: degree of return [5], level of recovery [208], magnitude of loss [209], recovery ability [61], [186], and recovery degree [4]. Additional publications included this concept without defining a metric [204], [210].…”

Section: Magnitude-based Metricsmentioning

confidence: 99%

Infrastructure resilience curves: Performance measures and summary metrics

Poulin

Kane

2021

Reliability Engineering & System Safety

115

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“…Bouloiz 45 ability to withstand shock and maintain critical function in order to keep a firm operating in varying conditions, even if these conditions are excepted or not. Small et al 46 ability to create through design choices an inherent system quality to maintain system performance objectives in the face of diverse operational challenges, in either a preparative or recovery sense, within acceptable time and cost parameters Lengnick-Hall et al 47 to effectively absorb, develop situation-specific responses to, and ultimately engage in transformative activities to capitalise on disruptive surprises that potentially threaten organisational survival Erol et al 48 interaction of the characteristics and capacities of a system, which will eventually evolve in the case of a disruptive event to adapt to an uncertain and changing environment and recover from the impacts of the disruptive event Park et al 49 the outcome of a recursive process that includes: sensing, anticipation, learning, adaptation where resilience is the emergent property of a system undergoing adaptive process -that is, not as something a system has, but a characteristic of the way it behaves preparing for and living with the unexpected, where hazards cannot be identified with certainty (c) to represent activities, diamonds (᭛) to represent gate-ways, and arrows (!) to represent connectors indicating sequence flow and direction.…”

Section: Author Definitionmentioning

confidence: 99%

Modelling workforce employability pipelines for organisational resilience

Jnitova

Joiner

Efatmaneshnik

et al. 2021

International Journal of Engineering Business Management

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Large organisations use both internal and external methods to educate their workforce. Workforce approaches in Defence were usually of a closed nature, characterised by entry at recruitment and sequential and hierarchical rank progression. More recently, emerging technology and the associated pace of societal change has required Defence to recruit more laterally and to outsource more education, both ab initio and development. The growing complexity of workforce problems, therefore, challenges military educational decision making to increase its focus on organisational resilience. Modelling and Simulation (M&S) can take messy, ill-defined problems and build models for decision support and problem-solving. M&S is being explored in Defence workforce employability planning to deliver education that is more resilient to perturbations and can more confidently predict graduate demand for educational support partnering. However, the effective use of M&S can be compromised if it is not cognitively useful for the problem owner. A new transformational approach between the modeller and the managers of Defence educational workforce is proposed and illustrated by two conceptual case studies. The method uses the module-based translation between Business Process Model Notation (BPMN) design patterns and systems dynamics building blocks to reduce the problem owner’s reliance on specialist modellers. This approach increases the cognitive effectiveness of proposed workforce education solutions and the sharing and reuse of workforce M&S applications. Any large organisation with sufficient human resource and systems engineering support could adopt this new approach to model and simulate their workforce education and examine their resilience to fluctuations.

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3.1.2 Exploring Resilience Measurement Methodologies

Cited by 13 publications

References 35 publications

Assessing Engineering Resilience for Systems with Multiple Performance Measures

Assessing Engineering Resilience for Systems with Multiple Performance Measures

Infrastructure resilience curves: Performance measures and summary metrics

Modelling workforce employability pipelines for organisational resilience

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