scholarly journals System reliability and component importance when components can be swapped upon failure

2018 ◽  
Vol 35 (3) ◽  
pp. 399-413 ◽  
Author(s):  
Aesha Najem ◽  
Frank P. A. Coolen
Keyword(s):  
System Reliability ◽  
Component Importance

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.

scholarly journals Computational method for importance measure of the k-out-of-n system based on stress–strength interference

2019 ◽  
Vol 234 (1) ◽  
pp. 27-40
Author(s):  
Dong Lyu ◽  
Shubin Si ◽  
Zhiqiang Cai ◽  
Liyang Xie
Keyword(s):  
System Reliability ◽  
Strength Distribution ◽  
Computational Method ◽  
Risk Assessments ◽  
System Level ◽  
Importance Measure ◽  
Relative Significance ◽  
Numerical Examples ◽  
Component Importance ◽  
Distribution Parameters

Importance measures, which are used to evaluate the relative significance of various components to system reliability, have been widely applied in system reliability designs and risk assessments. This article deals with the importance measure for the k-out-of- n system of which components are loaded by common stress. Based on system-level stress–strength interference model, a new computational method for the Birnbaum importance measure is proposed for the k-out-of- n system. Then, two numerical examples are presented to further illustrate the proposed method and some key contents are discussed particularly as follows: (1) the importance measures for the system with s-identical components and nonidentical components are developed, (2) component importance changes as its own strength distribution parameters change and (3) the new method corrects the errors caused by ignoring the failure dependency.

A New Concept for Assessing System Reliability Based on Probability Decomposition Method

2007 ◽  
Vol 353-358 ◽  
pp. 2525-2528
Author(s):  
Yang Pei ◽  
Bi Feng Song ◽  
Qing Han
Keyword(s):  
Failure Probability ◽  
System Reliability ◽  
Decomposition Method ◽  
Fault Tree Analysis ◽  
System Failure ◽  
Reliability Design ◽  
Critical States ◽  
Component Importance ◽  
Probability Concept ◽  
Probability Decomposition

In fault tree analysis, the system failure probability and the component importance measures cannot totally include the contribution of all the component existing states to system reliability. It is for this reason that an ‘equivalent’ failure probability concept is proposed. First, the system existing states are analyzed by probability decomposition method. Then Markov chain method and the expectation theory are used to calculate the expected working number resulting in system failure. And the system equivalent failure probability is finally attained. Analysis shows that: (1) equivalent failure probability not only includes the contribution of critical states of component to system reliability, but also the non-critical states of component are considered; and (2) it may provide a thorough assessment of system reliability and is useful for reliability design.

scholarly journals Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

2017 ◽  
Vol 2017 ◽  
pp. 1-18
Author(s):  
Shuai Lin ◽  
Yanhui Wang ◽  
Limin Jia ◽  
Yang Li
Keyword(s):  
System Reliability ◽  
Choquet Integral ◽  
Negative Impact ◽  
Construction Method ◽  
Centrality Measures ◽  
Importance Measure ◽  
Computation Method ◽  
Fuzzy Integral ◽  
Topological Network ◽  
Component Importance

In view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of components in electromechanical systems in this paper. ICMs are the meaningful extension of centrality measures and component importance measures, which consider influences on function and topology between components to increase importance measures usefulness. Our work makes two important contributions. First, we propose a novel integration method of component importance measures to define ICMs based on Choquet integral. Second, a meaningful fuzzy integral is first brought into the construction comprehensive measure by fusion multi-ICMs and then identification of important components which could give consideration to the function of components and topological structure of the whole system. In addition, the construction method of ICMs and comprehensive measure by integration multi-CIMs based on fuzzy integral are illustrated with a holistic topological network of bogie system that consists of 35 components.

scholarly journals Reliability Importance of Components in a Real-Time Computing System with Standby Redundancy Schemes

2018 ◽  
Vol 3 (2) ◽  
pp. 64-89 ◽  
Author(s):  
Junjun Zheng ◽  
Hiroyuki Okamura ◽  
Tadashi Dohi
Keyword(s):  
Real Time ◽  
System Reliability ◽  
High Reliability ◽  
Computing System ◽  
Performance Measure ◽  
Point Of View ◽  
Component Importance ◽  
Common Cause Failures ◽  
Importance Analysis ◽  
Real Time Computing

Component importance analysis is to measure the effect on system reliability of component reliabilities, and is used to the system design from the reliability point of view. On the other hand, to guarantee high reliability of real-time computing systems, redundancy has been widely applied, which plays an important role in enhancing system reliability. One of commonly used type of redundancy is the standby redundancy. However, redundancy increases not only the complexity of a system but also the complexity of associated problems such as common-mode error. In this paper, we consider the component importance analysis of a real-time computing system with warm standby redundancy in the presence of Common-Cause Failures (CCFs). Although the CCFs are known as a risk factor of degradation of system reliability, it is difficult to evaluate the component importance measures in the presence of CCFs analytically. This paper introduces a Continuous-Time Markov Chain (CTMC) model for real-time computing system, and applies the CTMC-based component-wise sensitivity analysis which can evaluate the component importance measures without any structure function of system. In numerical experiments, we evaluate the effect of CCFs by the comparison of system performance measure and component importance in the case of system without CCF with those in the case of system with CCFs. Also, we compare the effect of CCFs on the system in warm and hot standby configurations.

EFFECTIVE COMPONENT IMPORTANCE ANALYSIS FOR THE MAINTENANCE OF SYSTEMS WITH COMMON-CAUSE FAILURES

2007 ◽  
Vol 14 (05) ◽  
pp. 459-478 ◽  
Author(s):  
LIUDONG XING ◽  
SUPRASAD V. AMARI
Keyword(s):  
System Reliability ◽  
Selection Process ◽  
Common Cause ◽  
Component Importance ◽  
Important Concern ◽  
Common Cause Failures ◽  
Importance Analysis ◽  
System Maintenance ◽  
Maintenance Activities ◽  
Effective Component

In this paper, we consider the component importance analysis of coherent systems subject to common-cause failures. The purpose of component importance analysis is to obtain information regarding a component's contribution or importance to the system reliability. The results from the component importance analysis are key contributors to the system design, tuning, and maintenance activities. Various measures have been proposed for the component importance analysis, but little work has been done to compare their performance. In this research, we investigate and compare a set of nine existing importance measures and select the most informative and appropriate one for guiding the system maintenance activity. An important concern in the traditional fault tree reliability analysis, common-cause failures, is also considered in the component importance analysis. An example is designed and analyzed to show the selection process and to illustrate our efficient method for considering the effects of common-cause failures in the component importance analysis.

Resilience Assessment Based on Time-Dependent System Reliability Analysis

2016 ◽  
Author(s):  
Zhen Hu ◽  
Sankaran Mahadevan
Keyword(s):  
Reliability Analysis ◽  
System Reliability ◽  
Assessment Method ◽  
Time Dependent ◽  
Importance Measure ◽  
System Reliability Analysis ◽  
Component Importance ◽  
System Resilience ◽  
Resilience Assessment ◽  
Time Dependent System

Significant efforts have been recently devoted to the qualitative and quantitative evaluation of resilience in engineering systems. Current resilience evaluation methods, however, have mainly focused on business supply chains and civil infrastructure, and need to be extended for application in engineering design. A new resilience metric is proposed in this paper for the design of mechanical systems to bridge this gap, by investigating the effects of recovery activity and failure scenarios on system resilience. The defined resilience metric is connected to design through time-dependent system reliability analysis. This connection enables us to design a system for a specific resilience target in the design stage. Since computationally expensive computer simulations are usually used in design, a surrogate modeling method is developed to efficiently perform time-dependent system reliability analysis for resilience assessment. System resilience assessment is then investigated based on the developed time-dependent system reliability analysis method. The connection between the proposed resilience assessment method and design is discussed through the sensitivity analysis and component importance measure. Two numerical examples are used to illustrate the effectiveness of the proposed resilience assessment method and the associated sensitivity analysis and component importance measure.

Components Importance Analysis Fault Tree of Power Transformer of Gi Simangkuk Switchyard in Indonesia

2013 ◽  
Vol 694-697 ◽  
pp. 907-910 ◽  
Author(s):  
Josep Franklin Sihite ◽  
Takehisa Kohda
Keyword(s):  
System Reliability ◽  
Power Transformer ◽  
Fault Tree ◽  
Importance Measure ◽  
Component Importance ◽  
Safety Improvement ◽  
System Components ◽  
Importance Analysis

The purpose of this paper is to study the importance measures of power transformer system components. Importance measures analysis is a key part of the system reliability quantification process which are most effective towards safety improvement. This paper presented an application and results of the importance measures analysis of a power transformer system of GI Simangkuk switchyard in Indonesia by using Birnbaum importace measures, critically importance measure, and Fussel-Vessely importance measures. These method present the rank of the component importance measures quantitavily according to their contribution to system reliability and safety.

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