Reliability evaluation and component importance measure for manufacturing systems based on failure losses

2015 ◽  
Vol 28 (8) ◽  
pp. 1859-1869 ◽  
Author(s):  
Ding Zhang ◽  
Yingjie Zhang ◽  
Mingrang Yu ◽  
Yun Chen
Keyword(s):  
Manufacturing Systems ◽  
Reliability Evaluation ◽  
Importance Measure ◽  
Component Importance ◽  
Failure Losses

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 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

scholarly journals Measuring Component Importance for Network System Using Cellular Automata

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Li He ◽  
Qiyan Cao ◽  
Fengjun Shang
Keyword(s):  
Growth Factor ◽  
Cellular Automata ◽  
Numerical Experiments ◽  
Importance Measure ◽  
Network System ◽  
Failure Rates ◽  
Random Series ◽  
Component Importance ◽  
The Impact ◽  
Computing Method

This paper concentrates on the component importance measure of a network whose arc failure rates are not deterministic and imprecise ones. Conventionally, a computing method of component importance and a measure method of reliability stability are proposed. Three metrics are analyzed first: Birnbaum measurement, component importance, and component risk growth factor. Based on them, the latter can measure the impact of the component importance on the reliability stability of a system. Examples in some typical structures illustrate how to calculate component importance and reliability stability, including uncertain random series, parallel, parallel-series, series-parallel, and bridge systems. The comprehensive numerical experiments demonstrate that both of these methods can efficiently and accurately evaluate the impact of an arc failure on the reliability of a network system.

Representations of component importance for coherent systems with exchangeable components

2020 ◽  
Vol 57 (2) ◽  
pp. 385-406
Author(s):  
S. Pitzen ◽  
M. Burkschat
Keyword(s):  
Order Statistics ◽  
Distribution Functions ◽  
Importance Measure ◽  
Coherent Systems ◽  
Sequential Order ◽  
Limiting Behavior ◽  
Sequential Order Statistics ◽  
Component Importance ◽  
Dependent Component ◽  
Two Measures

AbstractTwo definitions of Birnbaum’s importance measure for coherent systems are studied in the case of exchangeable components. Representations of these measures in terms of distribution functions of the ordered component lifetimes are given. As an example, coherent systems with failure-dependent component lifetimes based on the notion of sequential order statistics are considered. Furthermore, it is shown that the two measures are ordered in the case of associated component lifetimes. Finally, the limiting behavior of the measures with respect to time is examined.

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.

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.

Component Reliability Importance Measure in Presence of Transient Faults

2011 ◽  
Vol 58-60 ◽  
pp. 529-534 ◽  
Author(s):  
Xin Qi ◽  
De C. Zuo ◽  
Zhan Zhang ◽  
Xiao Zong Yang
Keyword(s):  
Field Data ◽  
Importance Measure ◽  
Transient Faults ◽  
Composite Measure ◽  
Component Reliability ◽  
Component Importance ◽  
Importance Analysis ◽  
System Improvement ◽  
State Changes ◽  
Consistent Performance

Importance measures are widely used to characterize the contribution of components to the system performance such as reliability, availability, risk, etc, and thus give great help in identifying system weaknesses and prioritizing system improvement activities. Although much work has been carried out on component importance analysis, most studies only concern the consistent states of components within which components exhibit consistent performance until state changes happen. Unfortunately, field data shows that many transient faults in components may result in severe consequences without causing any state changes, and, this can lead to a misunderstanding of component importance. This paper focuses on the reliability importance analysis in presence of transient faults, and proposes a composite measure for evaluation. A sample series parallel system is analyzed to illustrate the use of this measure.

Reliability evaluation for multi-state manufacturing systems with quality-reliability dependency

2021 ◽  
Vol 154 ◽  
pp. 107166
Author(s):  
Zhaoxiang Chen ◽  
Zhen Chen ◽  
Di Zhou ◽  
Tangbin Xia ◽  
Ershun Pan
Keyword(s):  
Manufacturing Systems ◽  
Reliability Evaluation

Reliability evaluation and analysis of CNC cam shaft grinding machine

2015 ◽  
Vol 13 (1) ◽  
pp. 37-73 ◽  
Author(s):  
M.K. Loganathan ◽  
O.P. Gandhi
Keyword(s):  
System Reliability ◽  
Manufacturing Systems ◽  
Systems Approach ◽  
Reliability Evaluation ◽  
Point Of View ◽  
Graph Models ◽  
Content Type ◽  
Structural Graph ◽  
Hierarchical Levels ◽  
Grinding Machine

Purpose – Reliability assessment does require an effective structural modelling approach for systems, in general and manufacturing systems are no exception. This paper aims to develop it for large manufacturing systems using graph models, a systems approach. Design/methodology/approach – Structural graph models for reliability at various hierarchical levels are developed by considering a CNC cam shaft grinding machine. The system reliability expression is obtained by converting the reliability graphs into equivalent matrices, which helps to evaluate and analyse system. Findings – Using the obtained reliability expressions at various hierarchical levels of the system, it is possible not only to evaluate its reliability from structure point of view but also to identify weak structural elements from reliability point of view. Research limitations/implications – The approach can be extended to include the influence of other parameters, such as human, component and environment, etc., on the system reliability. Practical implications – The approach helps to design and develop manufacturing systems from reliability consideration by assessing their possible alternatives among these. Originality/value – The suggested methodology is useful for reliability evaluation of large and complex manufacturing systems.

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