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Resilience analysis: A formulation to model risk factors on complex system resilience

Resilience is about the ability of the system to resist, adapt to, and expeditiously recover from a disruptive event. The first and maybe the crucial step of resilience management is known as resilience analysis. However, there are many obstacles in front of the analyzers to analyze the resilience o...

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Autores principales: Mottahedi, Adel, Sereshki, Farhang, Ataei, Mohammad, Nouri Qarahasanlou, Ali, Barabadi, Abbas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130812/
http://dx.doi.org/10.1007/s13198-021-01131-w
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author Mottahedi, Adel
Sereshki, Farhang
Ataei, Mohammad
Nouri Qarahasanlou, Ali
Barabadi, Abbas
author_facet Mottahedi, Adel
Sereshki, Farhang
Ataei, Mohammad
Nouri Qarahasanlou, Ali
Barabadi, Abbas
author_sort Mottahedi, Adel
collection PubMed
description Resilience is about the ability of the system to resist, adapt to, and expeditiously recover from a disruptive event. The first and maybe the crucial step of resilience management is known as resilience analysis. However, there are many obstacles in front of the analyzers to analyze the resilience of systems. One of these obstacles is precise resilience data accessibility. Conventional resilience analysis methods frequently only consider historical data (e.g., time to repair and time to failure). However, to analyze the system resilience more precisely, the effect of the risk factors, which are known as observed and unobserved covariates, should be considered in the collected resilience database. These covariates will lead to the observed and unobserved heterogeneities among the collected database. Ignoring the effect of covariate may lead to erroneous conclusion about the resilience level of the system. Since it is hard to find a homogeneous operating condition, in this study, a formulation is proposed to model the effect of these covariates on complex system resilience. Finally, it is applied to a transportation system of a surface mine.
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spelling pubmed-81308122021-05-19 Resilience analysis: A formulation to model risk factors on complex system resilience Mottahedi, Adel Sereshki, Farhang Ataei, Mohammad Nouri Qarahasanlou, Ali Barabadi, Abbas Int J Syst Assur Eng Manag Original Article Resilience is about the ability of the system to resist, adapt to, and expeditiously recover from a disruptive event. The first and maybe the crucial step of resilience management is known as resilience analysis. However, there are many obstacles in front of the analyzers to analyze the resilience of systems. One of these obstacles is precise resilience data accessibility. Conventional resilience analysis methods frequently only consider historical data (e.g., time to repair and time to failure). However, to analyze the system resilience more precisely, the effect of the risk factors, which are known as observed and unobserved covariates, should be considered in the collected resilience database. These covariates will lead to the observed and unobserved heterogeneities among the collected database. Ignoring the effect of covariate may lead to erroneous conclusion about the resilience level of the system. Since it is hard to find a homogeneous operating condition, in this study, a formulation is proposed to model the effect of these covariates on complex system resilience. Finally, it is applied to a transportation system of a surface mine. Springer India 2021-05-18 2021 /pmc/articles/PMC8130812/ http://dx.doi.org/10.1007/s13198-021-01131-w Text en © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Mottahedi, Adel
Sereshki, Farhang
Ataei, Mohammad
Nouri Qarahasanlou, Ali
Barabadi, Abbas
Resilience analysis: A formulation to model risk factors on complex system resilience
title Resilience analysis: A formulation to model risk factors on complex system resilience
title_full Resilience analysis: A formulation to model risk factors on complex system resilience
title_fullStr Resilience analysis: A formulation to model risk factors on complex system resilience
title_full_unstemmed Resilience analysis: A formulation to model risk factors on complex system resilience
title_short Resilience analysis: A formulation to model risk factors on complex system resilience
title_sort resilience analysis: a formulation to model risk factors on complex system resilience
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130812/
http://dx.doi.org/10.1007/s13198-021-01131-w
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