The Resilience of Critical Infrastructure Systems: A Systematic Literature Review

Risk management is a fundamental approach to improving critical infrastructure systems’ safety against disruptive events. This approach focuses on designing robust critical infrastructure systems (CISs) that could resist disruptive events by minimizing the possible events’ probability and consequenc...

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Main Authors: Adel Mottahedi, Farhang Sereshki, Mohammad Ataei, Ali Nouri Qarahasanlou, Abbas Barabadi
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/6/1571
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spelling doaj-fb3f13d8536d47c896977ad6afd49a4d2021-03-13T00:02:12ZengMDPI AGEnergies1996-10732021-03-01141571157110.3390/en14061571The Resilience of Critical Infrastructure Systems: A Systematic Literature ReviewAdel Mottahedi0Farhang Sereshki1Mohammad Ataei2Ali Nouri Qarahasanlou3Abbas Barabadi4Faculty of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology, Shahrood 3619995161, IranFaculty of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology, Shahrood 3619995161, IranFaculty of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology, Shahrood 3619995161, IranFaculty of Technical and Engineering, Imam Khomeini International University, Qazvin 3414896818, IranDepartment of Technology and Safety, UiT the Arctic University of Norway, Tromsø 6050, NorwayRisk management is a fundamental approach to improving critical infrastructure systems’ safety against disruptive events. This approach focuses on designing robust critical infrastructure systems (CISs) that could resist disruptive events by minimizing the possible events’ probability and consequences using preventive and protective programs. However, recent disasters like COVID-19 have shown that most CISs cannot stand against all potential disruptions. Recently there is a transition from robust design to resilience design of CISs, increasing the focus on preparedness, response, and recovery. Resilient CISs withstand most of the internal and external shocks, and if they fail, they can bounce back to the operational phase as soon as possible using minimum resources. Moreover, in resilient CISs, early warning enables managers to get timely information about the proximity and development of distributions. An understanding of the concept of resilience, its influential factors, and available evaluation and analyzing tools are required to have effective resilience management. Moreover, it is important to highlight the current gaps. Technological resilience is a new concept associated with some ambiguity around its definition, its terms, and its applications. Hence, using the concept of resilience without understanding these variations may lead to ineffective pre- and post-disruption planning. A well-established systematic literature review can provide a deep understanding regarding the concept of resilience, its limitation, and applications. The aim of this paper is to conduct a systematic literature review to study the current research around technological CISs’ resilience. In the review, 192 primary studies published between 2003 and 2020 are reviewed. Based on the results, the concept of resilience has gradually found its place among researchers since 2003, and the number of related studies has grown significantly. It emerges from the review that a CIS can be considered as resilient if it has (i) the ability to imagine what to expect, (ii) the ability to protect and resist a disruption, (iii) the ability to absorb the adverse effects of disruption, (iv) the ability to adapt to new conditions and changes caused by disruption, and (v) the ability to recover the CIS’s normal performance level after a disruption. It was shown that robustness is the most frequent resilience contributing factor among the reviewed primary studies. Resilience analysis approaches can be classified into four main groups: empirical, simulation, index-based, and qualitative approaches. Simulation approaches, as dominant models, mostly study real case studies, while empirical methods, specifically those that are deterministic, are built based on many assumptions that are difficult to justify in many cases.https://www.mdpi.com/1996-1073/14/6/1571resiliencerobustnessrecoverabilitydisruptioncritical infrastructuretechnological CIS
collection DOAJ
language English
format Article
sources DOAJ
author Adel Mottahedi
Farhang Sereshki
Mohammad Ataei
Ali Nouri Qarahasanlou
Abbas Barabadi
spellingShingle Adel Mottahedi
Farhang Sereshki
Mohammad Ataei
Ali Nouri Qarahasanlou
Abbas Barabadi
The Resilience of Critical Infrastructure Systems: A Systematic Literature Review
Energies
resilience
robustness
recoverability
disruption
critical infrastructure
technological CIS
author_facet Adel Mottahedi
Farhang Sereshki
Mohammad Ataei
Ali Nouri Qarahasanlou
Abbas Barabadi
author_sort Adel Mottahedi
title The Resilience of Critical Infrastructure Systems: A Systematic Literature Review
title_short The Resilience of Critical Infrastructure Systems: A Systematic Literature Review
title_full The Resilience of Critical Infrastructure Systems: A Systematic Literature Review
title_fullStr The Resilience of Critical Infrastructure Systems: A Systematic Literature Review
title_full_unstemmed The Resilience of Critical Infrastructure Systems: A Systematic Literature Review
title_sort resilience of critical infrastructure systems: a systematic literature review
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2021-03-01
description Risk management is a fundamental approach to improving critical infrastructure systems’ safety against disruptive events. This approach focuses on designing robust critical infrastructure systems (CISs) that could resist disruptive events by minimizing the possible events’ probability and consequences using preventive and protective programs. However, recent disasters like COVID-19 have shown that most CISs cannot stand against all potential disruptions. Recently there is a transition from robust design to resilience design of CISs, increasing the focus on preparedness, response, and recovery. Resilient CISs withstand most of the internal and external shocks, and if they fail, they can bounce back to the operational phase as soon as possible using minimum resources. Moreover, in resilient CISs, early warning enables managers to get timely information about the proximity and development of distributions. An understanding of the concept of resilience, its influential factors, and available evaluation and analyzing tools are required to have effective resilience management. Moreover, it is important to highlight the current gaps. Technological resilience is a new concept associated with some ambiguity around its definition, its terms, and its applications. Hence, using the concept of resilience without understanding these variations may lead to ineffective pre- and post-disruption planning. A well-established systematic literature review can provide a deep understanding regarding the concept of resilience, its limitation, and applications. The aim of this paper is to conduct a systematic literature review to study the current research around technological CISs’ resilience. In the review, 192 primary studies published between 2003 and 2020 are reviewed. Based on the results, the concept of resilience has gradually found its place among researchers since 2003, and the number of related studies has grown significantly. It emerges from the review that a CIS can be considered as resilient if it has (i) the ability to imagine what to expect, (ii) the ability to protect and resist a disruption, (iii) the ability to absorb the adverse effects of disruption, (iv) the ability to adapt to new conditions and changes caused by disruption, and (v) the ability to recover the CIS’s normal performance level after a disruption. It was shown that robustness is the most frequent resilience contributing factor among the reviewed primary studies. Resilience analysis approaches can be classified into four main groups: empirical, simulation, index-based, and qualitative approaches. Simulation approaches, as dominant models, mostly study real case studies, while empirical methods, specifically those that are deterministic, are built based on many assumptions that are difficult to justify in many cases.
topic resilience
robustness
recoverability
disruption
critical infrastructure
technological CIS
url https://www.mdpi.com/1996-1073/14/6/1571
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