Multidimensional approach to complex system resilience analysis

Dessavre, Dante Gama; Ramírez-Márquez, José Emmanuel; Barker, Kash

doi:10.1016/j.ress.2015.12.009

Cited by 112 publications

(51 citation statements)

References 11 publications

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“…The authors defined three distinct states, namely: original stable (S0), disrupted (Sd), and stable recovered (Sf) that depict the states of any system before, during, and after the occurrence of a hazard, respectively. Equation (2) is used to calculate the resilience as a ratio between the recovery level at any instant to the initial loss in the performance function [18][19][20][21]. Figure 1.…”

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

“…At that instant, the system undergoes a transition state beginning with a gradual its performance, followed by an idle period for damage estimation and restoration is transition finally ends by a course of recovery actions to restore service provision. The ed steady state may be either same, less, or even more than the initial state before the ccurrence [21].…”

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

“…F (t r |e j ) is the proportion of delivery function that has been recovered from the disrupted state under event e j , F(t r e j ) is the figure-of-merit of the system at the recovered state t r , F(t d e j ) is the figure-of-merit of the system at the disrupted state t d under the event e j . Dessavre et al [21] formulated a five-states resilience framework for assessing the resilience of urban infrastructure systems before, during, and after the disruption events. Figure 2 illustrates their model, starting from a steady reliability state when a system functions normally before the occurrence of a disruptive event.…”

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

“…This transition finally ends by a course of recovery actions to restore service provision. The final recovered steady state may be either same, less, or even more than the initial state before the disruption occurrence [21]. Ouyang et al [22] extended previous approaches to present a stochastic time-dependent metric for measuring the annual resilience against multi-hazard events.…”

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

See 4 more Smart Citations

A New Metric for Assessing Resilience of Water Distribution Networks

Assad

Moselhi

Zayed

2019

Water

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Water distribution networks (WDNs) face various types of hazards during their extended life. Ensuring proper functioning of WDNs has always been a major concern for utility managers because of their impact on public health and safety. Resilience is an emerging concept that aims at maintaining functionality of the WDNs. Most of the previously developed resilience frameworks employed simulation methods to assess resilience of the WDNs, focusing only on the specific aspects of resilience. There is a need to develop a holistic approach to evaluate the resilience of WDNs considering various dimensions of resilience. This paper presents a new multi-attribute resilience metric based on the robustness and redundancy of the WDNs, which can be used to achieve the purpose. The developed metric is used to evaluate the resilience of a WDN in the city of London, Ontario. An optimization framework for enhancing the current resilience level is also presented. Resilience of the network is found to increase around 20% with a $500,000 investment. A hazard scenario is then analyzed to illustrate the practicality of using this metric in selecting effective restoration strategies. The proposed metric can be utilized by water agencies to evaluate and enhance the resilience of WDNs, as well as to optimize the recovery process after disruptive events.

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Section: = ∫ [100 − ( )]mentioning

confidence: 99%

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

Section: = ∫ [100 − ( )]mentioning

confidence: 99%

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A New Metric for Assessing Resilience of Water Distribution Networks

Assad

Moselhi

Zayed

2019

Water

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Resilience Engineering and Management

2018

Reliability Engineering and Service

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A systems perspective on contact centers and customer service reliability modeling

Andrade

Moazeni

Ramírez-Márquez

2019

Systems Engineering

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Contact centers play a critical role in service businesses by acting as the interface between customers and organizations. They are strategic tools to establish a relationship with customers to promote customer satisfaction, which can lead to an increase in customer loyalty and sales. One important factor impacting customer satisfaction is service reliability, which should be constantly monitored to enhance customer satisfaction. This paper uses a systems thinking approach to investigate contact centers from a systems perspective. We aim to provide a holistic view of the customer support process to help decision makers infer transformations in the system. We present an architecture of the contact center operations management system incorporating concepts of systems engineering, and describe its components and functions. The systems perspective to contact center processes facilitates developing a customer service reliability model. Since the reliability metric takes into account the fundamentals of the contact center processes and key input data, the modeling approach can dynamically adapt to changes in the contact center processes and data. The developed system architecture and reliability metric are general and adaptable to be expanded to other domains. An empirical analysis using data from a major insurance company is provided to illustrate the applicability of the system design, reliability, and performance control using a control chart.

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Multidimensional approach to complex system resilience analysis

Cited by 112 publications

References 11 publications

A New Metric for Assessing Resilience of Water Distribution Networks

A New Metric for Assessing Resilience of Water Distribution Networks

Resilience Engineering and Management

A systems perspective on contact centers and customer service reliability modeling

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