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Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components

The degradation and recovery processes are multi-scale phenomena in many physical, engineering, biological, and social systems, and determine the aging of the entire system. Therefore, understanding the interplay between the two processes at the component level is the key to evaluate the reliability...

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Detalles Bibliográficos
Autores principales: Du, Yi-Mu, Chen, Jin-Fu, Guan, Xuefei, Sun, C. P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001036/
https://www.ncbi.nlm.nih.gov/pubmed/33804116
http://dx.doi.org/10.3390/e23030348
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author Du, Yi-Mu
Chen, Jin-Fu
Guan, Xuefei
Sun, C. P.
author_facet Du, Yi-Mu
Chen, Jin-Fu
Guan, Xuefei
Sun, C. P.
author_sort Du, Yi-Mu
collection PubMed
description The degradation and recovery processes are multi-scale phenomena in many physical, engineering, biological, and social systems, and determine the aging of the entire system. Therefore, understanding the interplay between the two processes at the component level is the key to evaluate the reliability of the system. Based on the principle of maximum entropy, an approach is proposed to model and infer the processes at the component level, and is applied to repairable and non-repairable systems. By incorporating the reliability block diagram, this approach allows for integrating the information of network connectivity and statistical moments to infer the hazard or recovery rates of the degradation or recovery processes. The overall approach is demonstrated with numerical examples.
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spelling pubmed-80010362021-03-28 Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components Du, Yi-Mu Chen, Jin-Fu Guan, Xuefei Sun, C. P. Entropy (Basel) Article The degradation and recovery processes are multi-scale phenomena in many physical, engineering, biological, and social systems, and determine the aging of the entire system. Therefore, understanding the interplay between the two processes at the component level is the key to evaluate the reliability of the system. Based on the principle of maximum entropy, an approach is proposed to model and infer the processes at the component level, and is applied to repairable and non-repairable systems. By incorporating the reliability block diagram, this approach allows for integrating the information of network connectivity and statistical moments to infer the hazard or recovery rates of the degradation or recovery processes. The overall approach is demonstrated with numerical examples. MDPI 2021-03-15 /pmc/articles/PMC8001036/ /pubmed/33804116 http://dx.doi.org/10.3390/e23030348 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Du, Yi-Mu
Chen, Jin-Fu
Guan, Xuefei
Sun, C. P.
Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
title Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
title_full Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
title_fullStr Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
title_full_unstemmed Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
title_short Maximum Entropy Approach to Reliability of Multi-Component Systems with Non-Repairable or Repairable Components
title_sort maximum entropy approach to reliability of multi-component systems with non-repairable or repairable components
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001036/
https://www.ncbi.nlm.nih.gov/pubmed/33804116
http://dx.doi.org/10.3390/e23030348
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