Bayesian networks for system reliability reassessment

Mahadevan, Sankaran; Zhang, Ruoxue; Smith, Natasha

doi:10.1016/s0167-4730(01)00017-0

Cited by 242 publications

(99 citation statements)

References 18 publications

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“…If this methodology is developed further, the goal of investigations seems to be, in particular, application of Bayesian networks in the computational model [12,13], which describes propagation of fatigue cracks in the system. This contribution has been developed as a part of the research project GACR 17-01589S "Advanced computational and probabilistic modelling of steel structures taking account fatigue damage" supported by the Czech Grant Agency and also has been completed thanks to the financial support provided to VSB-Technical University of Ostrava by the Czech Ministry of Education, Youth and Sports from the budget for conceptual development of science, research and innovations for the 2017 year.…”

Section: Resultsmentioning

confidence: 99%

Using DOProC method in reliability assessment of steel elements exposed to fatigue

et al. 2017

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Abstract. Fatigue crack damage depends on a number of stress range cycles. This is a time factor in the course of reliability for the entire designed service life. Three sizes are important for the characteristics of the propagation of fatigue cracks -initial size, detectable size and acceptable size. The theoretical model of fatigue crack progression can be based on a linear fracture mechanic. Depending on location of an initial crack, the crack may propagate in structural element e.g. from the edge or from the surface. When determining the required degree of reliability, it is possible to specify the time of the first inspection of the construction which will focus on the fatigue damage. Using a conditional probability and Bayesian approach, times for subsequent inspections can be determined. For probabilistic modelling of fatigue crack progression was used the original and new probabilistic method -the Direct Optimized Probabilistic Calculation ("DOProC"), which uses a purely numerical approach without any simulation techniques or approximation approach based on optimized numerical integration.

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Section: Resultsmentioning

confidence: 99%

Using DOProC method in reliability assessment of steel elements exposed to fatigue

et al. 2017

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“…There has been an increase trend in the application of Bayesian networks in fields related to reliability, safety and maintenance (Mahadevan et al, 2001). Bayesian approaches to aggregate expert judgments on probabilities have been extensively investigated in risk and reliability analysis (Mosleh, 1986;Droguett et al, 2004;Podofillini and Dang, 2013).…”

Section: Bayesian Belief Network Modellingmentioning

confidence: 99%

Probabilistic risk analysis in manufacturing situational operation: application of modelling techniques and causal structure to improve safety performance.

Pereira

Lima

2015

Int. J. Prod. Manag. Eng.

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The use of probabilistic risk analysis in jet engines manufacturing process is essential to prevent failure. The objective of this study is to present a probabilistic risk analysis model to analyze the safety of this process. The standard risk assessment normally conducted is inadequate to address the risks. To remedy this problem, the model presented in this paper considers the effects of human, software and calibration reliability in the process. Bayesian Belief Network coupled to a Bow Tie diagram is used to identify potential engine failure scenarios. In this context and to meet this objective, an in depth literature research was conducted to identify the most appropriate modeling techniques and an interview were conducted with experts. As a result of this study, this paper presents a model that combines fault tree analysis, event tree analysis and a Bayesian Belief Networks into a single model that can be used by decision makers to identify critical risk factors in order to allocate resources to improve the safety of the system. The model is delivered in the form of a computer assisted decision tool supported by subject expert estimates.

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“…However, we cannot include that in our discussion because special software is necessary to adopt their methodology. On the other hand, Mahadevan et al [12] propose a methodology to apply a Bayesian network to structure system reliability reassessment. Some cases of its effectiveness have been shown, for example, in the field of architecture.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, this paper would propose a sustainable production planning model using the ranked positional weight technique and the inference and assessment methodology suggested by Mahadevan et al [12] to large scale problems. The conceptual flow of Mahadevan et al [12] is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Analysis to Achieve Sustainable Production Planning in Uncertain Environments

Kataoka

Morikawa

Takahashi

2015

Int J Jpn Assoc Mgt Sys

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Bayesian networks for system reliability reassessment

Cited by 242 publications

References 18 publications

Using DOProC method in reliability assessment of steel elements exposed to fatigue

Using DOProC method in reliability assessment of steel elements exposed to fatigue

Probabilistic risk analysis in manufacturing situational operation: application of modelling techniques and causal structure to improve safety performance.

A Comprehensive Analysis to Achieve Sustainable Production Planning in Uncertain Environments

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