Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation

Mingyang Li, Jian Liu, Jing Li, Byoung Uk Kim

Research output: Contribution to journalArticle

42 Citations (Scopus)

Abstract

Reliability modeling of multi-state hierarchical systems is challenging because of the complex system structures and imbalanced reliability information available at different system levels. This paper proposes a Bayesian multi-level information aggregation approach to model the reliability of multi-level hierarchical systems by utilizing all available reliability information throughout the system. Cascading failure dependency among components and/or sub-systems at the same level is explicitly considered. The proposed methodology can significantly improve the accuracy of system-level reliability modeling. A case study demonstrates the effectiveness of the proposed methodology.

Original languageEnglish (US)
Pages (from-to)158-164
Number of pages7
JournalReliability Engineering and System Safety
Volume124
DOIs
StatePublished - Apr 2014

Fingerprint

Multi-state System
Hierarchical systems
Bayesian Modeling
Hierarchical Systems
Reliability Modeling
Aggregation
Agglomeration
Cascading Failure
Methodology
Complex Systems
Subsystem
Large scale systems
Demonstrate
Model

Keywords

  • Bayesian networks
  • Hierarchical structure
  • Multiple failure states
  • Prior elicitation
  • System reliability

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality
  • Applied Mathematics

Cite this

Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation. / Li, Mingyang; Liu, Jian; Li, Jing; Uk Kim, Byoung.

In: Reliability Engineering and System Safety, Vol. 124, 04.2014, p. 158-164.

Research output: Contribution to journalArticle

@article{92576abc7a234cf5b7e68b21fc97a1e8,
title = "Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation",
abstract = "Reliability modeling of multi-state hierarchical systems is challenging because of the complex system structures and imbalanced reliability information available at different system levels. This paper proposes a Bayesian multi-level information aggregation approach to model the reliability of multi-level hierarchical systems by utilizing all available reliability information throughout the system. Cascading failure dependency among components and/or sub-systems at the same level is explicitly considered. The proposed methodology can significantly improve the accuracy of system-level reliability modeling. A case study demonstrates the effectiveness of the proposed methodology.",
keywords = "Bayesian networks, Hierarchical structure, Multiple failure states, Prior elicitation, System reliability",
author = "Mingyang Li and Jian Liu and Jing Li and {Uk Kim}, Byoung",
year = "2014",
month = "4",
doi = "10.1016/j.ress.2013.12.001",
language = "English (US)",
volume = "124",
pages = "158--164",
journal = "Reliability Engineering and System Safety",
issn = "0951-8320",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - Bayesian modeling of multi-state hierarchical systems with multi-level information aggregation

AU - Li, Mingyang

AU - Liu, Jian

AU - Li, Jing

AU - Uk Kim, Byoung

PY - 2014/4

Y1 - 2014/4

N2 - Reliability modeling of multi-state hierarchical systems is challenging because of the complex system structures and imbalanced reliability information available at different system levels. This paper proposes a Bayesian multi-level information aggregation approach to model the reliability of multi-level hierarchical systems by utilizing all available reliability information throughout the system. Cascading failure dependency among components and/or sub-systems at the same level is explicitly considered. The proposed methodology can significantly improve the accuracy of system-level reliability modeling. A case study demonstrates the effectiveness of the proposed methodology.

AB - Reliability modeling of multi-state hierarchical systems is challenging because of the complex system structures and imbalanced reliability information available at different system levels. This paper proposes a Bayesian multi-level information aggregation approach to model the reliability of multi-level hierarchical systems by utilizing all available reliability information throughout the system. Cascading failure dependency among components and/or sub-systems at the same level is explicitly considered. The proposed methodology can significantly improve the accuracy of system-level reliability modeling. A case study demonstrates the effectiveness of the proposed methodology.

KW - Bayesian networks

KW - Hierarchical structure

KW - Multiple failure states

KW - Prior elicitation

KW - System reliability

UR - http://www.scopus.com/inward/record.url?scp=84891755674&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84891755674&partnerID=8YFLogxK

U2 - 10.1016/j.ress.2013.12.001

DO - 10.1016/j.ress.2013.12.001

M3 - Article

AN - SCOPUS:84891755674

VL - 124

SP - 158

EP - 164

JO - Reliability Engineering and System Safety

JF - Reliability Engineering and System Safety

SN - 0951-8320

ER -