scholarly journals Birnbaum's measure of component importance for noncoherent systems

2003 ◽  
Vol 52 (2) ◽  
pp. 213-219 ◽  
Author(s):  
J.D. Andrews ◽  
S. Beeson
Keyword(s):  
Component Importance

scholarly journals Identifying Sensitive Components in Infrastructure Networks via Critical Flows

2019 ◽  
Author(s):  
James Williams
Keyword(s):  
Reliability Analysis ◽  
Critical Infrastructure ◽  
Urban Systems ◽  
Centrality Measures ◽  
Critical Flow ◽  
Infrastructure Networks ◽  
Component Importance ◽  
Infrastructure System ◽  
Critical Components ◽  
The Impact

This paper introduces a novel set of component importance measures that are based on the concept of critical flow. Various research communities have developed techniques for identifying critical components of networks. The methods in this paper extend previous work on flow-based centrality measures by adapting them to the assessment of critical infrastructure in urban systems. The motivation is to provide municipalities with a means of reasoning about the impact of urban interventions. An infrastructure system is represented as a flow network in which demand nodes are assigned both demand values and criticality ratings. Sensitive elements in the network are those that carry critical flows, where a flow is deemed critical to the extent that it satisfies critical demand. A method for computing these flows is presented, and its utility is demonstrated by comparing the new measures to existing flow centrality measures. The paper also shows how the method may be combined with standard approaches to reliability analysis.

scholarly journals An Overview of Various Importance Measures of Reliability System

2017 ◽  
Vol 2 (3) ◽  
pp. 150-171 ◽  
Author(s):  
Kalpesh P. Amrutkar ◽  
Kirtee K. Kamalja
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
System Failure ◽  
Numerical Rank ◽  
Reliability Improvement ◽  
System Reliability Analysis ◽  
Component Importance ◽  
Critical Components ◽  
The Impact ◽  
Reliability Systems

One of the purposes of system reliability analysis is to identify the weaknesses or the critical components in a system and to quantify the impact of component’s failures. Various importance measures are being introduced by many researchers since 1969. These component importance measures provide a numerical rank to determine which components are more important to system reliability improvement or more critical to system failure. In this paper, we overview various components importance measures and briefly discuss them with examples. We also discuss some other extended importance measures and review the developments in study of various importance measures with respect to some of the popular reliability systems.

COMBINATORIAL APPROACH TO COMPUTING COMPONENT IMPORTANCE INDEXES IN COHERENT SYSTEMS

2011 ◽  
Vol 26 (1) ◽  
pp. 117-128 ◽  
Author(s):  
Ilya B. Gertsbakh ◽  
Yoseph Shpungin
Keyword(s):  
System Reliability ◽  
Simple Formula ◽  
Analytic Formula ◽  
Importance Measure ◽  
Coherent Systems ◽  
Joint Reliability ◽  
Component Importance ◽  
Definition Of ◽  
Combinatorial Parameter ◽  
Combinatorial Representation

We consider binary coherent systems with independent binary components having equal failure probability q. The system DOWN probability is expressed via its signature's combinatorial analogue, the so-called D-spectrum. Using the definition of the Birnbaum importance measure (BIM), we introduce for each component a new combinatorial parameter, so-called BIM-spectrum, and develop a simple formula expressing component BIM via the component BIM-spectrum. Further extension of this approach allows obtaining a combinatorial representation for the joint reliability importance (JRI) of two components. To estimate component BIMs and JRIs, there is no need to know the analytic formula for system reliability. We demonstrate how our method works using the Monte Carlo approach. We present several examples of estimating component importance measures in a network when the DOWN state is defined as the loss of terminal connectivity.

Resilience‐based component importance measures

2019 ◽  
Vol 30 (11) ◽  
pp. 4244-4254
Author(s):  
Meilin Wen ◽  
Yubing Chen ◽  
Yi Yang ◽  
Rui Kang ◽  
Yanbo Zhang
Keyword(s):  
Component Importance

scholarly journals Component importance in coherent systems with exchangeable components

2015 ◽  
Vol 52 (3) ◽  
pp. 851-863 ◽  
Author(s):  
Serkan Eryilmaz
Keyword(s):  
Importance Measure ◽  
Coherent System ◽  
Coherent Systems ◽  
System A ◽  
Component Importance

This paper is concerned with the Birnbaum importance measure of a component in a binary coherent system. A representation for the Birnbaum importance of a component is obtained when the system consists of exchangeable dependent components. The results are closely related to the concept of the signature of a coherent system. Some examples are presented to illustrate the results.

Resiliency as a component importance measure in network reliability

2009 ◽  
Vol 94 (10) ◽  
pp. 1685-1693 ◽  
Author(s):  
John C. Whitson ◽  
Jose Emmanuel Ramirez-Marquez
Keyword(s):  
Network Reliability ◽  
Importance Measure ◽  
Component Importance
Sign in / Sign up

Export Citation Format

Share Document