Component-based system reliability subject to positive and negative correlation

Jafary, Bentolhoda; Mele, Andrew; Fiondella, Lance

doi:10.1016/j.ress.2020.107058

Cited by 13 publications

(4 citation statements)

References 29 publications

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“…For simplicity, the component-level RULs are assumed to be independent, but this assumption may not hold when considering failure-dependent manufacturing systems, resulting in unsatisfactory evaluation of the system reliability. There are some commonly used methods to consider the correlation between component life [8]: (1) multivariate distribution such as multivariate lognormal distribution [9], Marshall-Olkin Weibull distribution [10], and multivariate Birnbaum-Saunders distribution [11]; (2) combined effects of positive and negative correlations [12]; and (3) copula functions. In recent years, modeling the failure correlation between components via copula functions has attracted a lot of attention from researchers, mostly due to its advantage of flexibility.…”

Section: Literature Reviewmentioning

confidence: 99%

Reliability Analysis of Failure-Dependent System Based on Bayesian Network and Fuzzy Inference Model

Xiang

et al. 2023

Electronics

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With the rapid development of information and automation technology, the manufacturing system is evolving towards more complexity and integration. The system components will inevitably suffer from degeneration, and the impact of component-level failure on the system reliability is a valuable issue to be studied, especially when failure dependence exists among the components. Thus, it is vital to construct a system reliability evaluation mechanism that helps to characterize the healthy status of the system and facilitate wise decision making. In this paper, a reliability analysis framework for a failure-dependent system is proposed, in which copula functions with optimized parameters are used for the description of different failure correlations, and a fuzzy inference model is constructed to derive the subsystem reliability based on the component-level failure correlation. Finally, a Bayesian network is applied to infer the system reliability based on the system structure combined with the impact of failure correlation inside. Simulation results of the proposed method show that the inference results of system reliability are reasonable and effective in different cases. Compared with the copula Bayesian network method, the proposed method shows better adaptability to failure-dependent systems to varying degrees. This work can provide theoretical guidance for evaluating the reliability of manufacturing systems of different types.

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Section: Literature Reviewmentioning

confidence: 99%

Reliability Analysis of Failure-Dependent System Based on Bayesian Network and Fuzzy Inference Model

Xiang

et al. 2023

Electronics

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“…Correlation failure is a common issue in mechanical structures [1]. Traditional reliability modeling and analysis methods often assume independence, disregarding the impact of correlation on reliability [2]. To ensure accurate reliability calculations, it is essential to consider the correlation pattern (such as positive or negative correlation, homotopy, functional relationship, etc.)…”

Section: Introductionmentioning

confidence: 99%

“…In structural reliability engineering, correlation features primarily arise from stress and strength components, stress-strength [5,6], multiple failure mechanisms [7][8][9], and multiple parts [2,10]. Accurately quantifying and characterizing these correlation features is crucial for constructing a reliable structural analysis and calculation model.…”

Section: Introductionmentioning

confidence: 99%

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A Structural Reliability Analysis Method Considering Multiple Correlation Features

Bai,

Li,

Zhang

et al. 2024

Machines

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The paper analyzes the correlation features between stress strength, multiple failure mechanisms, and multiple components. It investigates the effects of different correlation features on reliability and proposes a method for structural reliability analysis that considers the joint effects of multiple correlation features. To portray the stress–strength correlation structure, the Copula function is utilized and the influence of the correlation degree parameter on reliability is clarified. The text describes the introduction of time-varying characteristics of structural strength and correlation parameters. A time-varying Copula is then constructed to calculate the structural reliability under the stress–strength correlation characteristics. Additionally, a time-varying hybrid Copula is constructed to characterize the intricate and correlation features of multiple failure mechanisms and components. The article proposes the variational adaptive sparrow search algorithm (VASSA) to obtain optimal parameters for the time-varying hybrid Copula. The effectiveness and accuracy of the proposed method are verified through actual cases. The results indicate that multiple correlation features significantly influence structural reliability. Incorporating multiple correlation features into the solution of structural reliability yields safer results that align with engineering practice.

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Series System Reliability: An Unified Approach Using Fatal Shock and Stress Models

Oliveira

Peres

Bertoli

et al. 2022

Springer Series in Reliability Engineering

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Component-based system reliability subject to positive and negative correlation

Cited by 13 publications

References 29 publications

Reliability Analysis of Failure-Dependent System Based on Bayesian Network and Fuzzy Inference Model

Reliability Analysis of Failure-Dependent System Based on Bayesian Network and Fuzzy Inference Model

A Structural Reliability Analysis Method Considering Multiple Correlation Features

Series System Reliability: An Unified Approach Using Fatal Shock and Stress Models

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