scholarly journals Reliability Modeling and Evaluation of Complex Multi-State System Based on Bayesian Networks Considering Fuzzy Dynamic of Faults

2021 ◽  
Vol 129 (2) ◽  
pp. 993-1012
Author(s):  
Fangjun Zuo ◽  
Meiwei Jia ◽  
Guang Wen ◽  
Huijie Zhang ◽  
Pingping Liu
Keyword(s):  
Bayesian Networks ◽  
State System ◽  
Reliability Modeling

Improved reliability modeling using Bayesian networks and dynamic discretization

2010 ◽  
Vol 95 (4) ◽  
pp. 412-425 ◽  
Author(s):  
David Marquez ◽  
Martin Neil ◽  
Norman Fenton
Keyword(s):  
Bayesian Networks ◽  
Reliability Modeling

Bayesian Networks Application in Multi-State System Reliability Analysis

2013 ◽  
Vol 347-350 ◽  
pp. 2590-2595 ◽  
Author(s):  
Sheng Zhai ◽  
Shu Zhong Lin
Keyword(s):  
Bayesian Network ◽  
Reliability Analysis ◽  
System Reliability ◽  
Prior Probability ◽  
State System ◽  
Weak Links ◽  
Uncertain Reasoning ◽  
Reliability Modeling ◽  
Line System ◽  
Reliability Indices

Aiming at the limitations of traditional reliability analysis theory in multi-state system, a method for reliability modeling and assessment of a multi-state system based on Bayesian Network (BN) is proposed with the advantages of uncertain reasoning and describing multi-state of event. Through the case of cell production line system, in this paper we will discuss how to establish and construct a multi-state system model based on Bayesian network, and how to apply the prior probability and posterior probability to do the bidirectional inference analysis, and directly calculate the reliability indices of the system by means of prior probability and Conditional Probability Table (CPT) . Thereby we can do the qualitative and quantitative analysis of the multi-state system reliability, identify the weak links of the system, and achieve assessment of system reliability.

Human Reliability Modeling of Radiotherapy Procedures by Bayesian Networks and Expert Opinion Elicitation

2016 ◽  
Vol 194 (1) ◽  
pp. 73-96 ◽  
Author(s):  
E. C. Gomes ◽  
J. P. Duarte ◽  
P. F. Frutuoso e Melo
Keyword(s):  
Bayesian Networks ◽  
Expert Opinion ◽  
Human Reliability ◽  
Reliability Modeling

Reliability modeling for a discrete time multi-state system with random and dependent transition probabilities

2019 ◽  
Vol 233 (5) ◽  
pp. 747-760 ◽  
Author(s):  
Linmin Hu ◽  
Rui Peng
Keyword(s):  
Discrete Time ◽  
Power Distribution ◽  
State Transition ◽  
Transition Probabilities ◽  
Survival Function ◽  
Copula Function ◽  
State System ◽  
Dependence Structure ◽  
Reliability Modeling ◽  
Dynamic Reliability

In a random environment, state transition probabilities of a multi-state system can change as the environment changes. Thus, a dynamic reliability model with random and dependent transition probabilities is developed for non-repairable discrete-time multi-state system in this article. The dependence among the random state transition probabilities of the system is modeled by a copula function. By probability argument and random process theory, we obtain explicit expressions of some reliability characteristics and joint survival function of random time spent by the system in all working states (partially and completely working states). A special case is considered when the state transition probabilities are dependent random variables with power distribution, and the dependence structure is modeled by Farlie–Gumbel–Morgenstern copula. Numerical examples are also presented to demonstrate the developed model and perform a comparison for the models with random and fixed transition probabilities.

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