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Journal ArticleDOI

Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches

TLDR
The paper concludes that BN is a superior technique in safety analysis because of its flexible structure, allowing it to fit a wide variety of accident scenarios.
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This article is published in Reliability Engineering & System Safety.The article was published on 2011-08-01. It has received 573 citations till now. The article focuses on the topics: Fault tree analysis & System safety.

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Citations
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Journal ArticleDOI

An elicitation process to quantify Bayesian networks for dam failure analysis

TL;DR: Bayesian networks support the probabilistic failure analysis of complex systems, e.g. dams and bridges, needed for a better understanding of the system reliability and for taking mitigation actions to reduce the risk of system failure.
Journal ArticleDOI

Managing infrastructure asset: Bayesian networks for inspection and maintenance decisions reasoning and planning

TL;DR: Bayesian networks are applied to allow inference of multi-state condition prediction, and further extend it to predict the condition of an asset with multiple components to plan maintenance activities for an asset over its whole life cycle.
Journal ArticleDOI

New Risk Methodology Based on Control Charts to Assess Occupational Risks in Manufacturing Processes.

TL;DR: A new dynamic methodology called Statistical Risk Control (SRC) based on Bayesian inference, control charts and analysis of the hidden Markov chain is presented to detect a situation outside the limits early enough to allow corrective actions to reduce the risk before an accident occurs.
Journal ArticleDOI

Capsizing accident scenario model for small fishing trawler

TL;DR: In this paper , the authors proposed applying the Object-Oriented Bayesian Network (OOBN) to capture the risk influencing factors of the capsizing accident scenario under different operating conditions for a small fishing trawler, a sub-class of fishing vessels.
Journal ArticleDOI

Reliability based rehabilitation of water distribution networks by means of Bayesian networks

TL;DR: In this paper, a static-dynamic Bayesian network (SBN) is used to predict the failure scenario regarding water distribution and a relationship between reliability and prioritization of rehabilitation actions has been investigated.
References
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Book

Bayesian networks and decision graphs

TL;DR: The book introduces probabilistic graphical models and decision graphs, including Bayesian networks and influence diagrams, and presents a thorough introduction to state-of-the-art solution and analysis algorithms.
Journal ArticleDOI

Improving the analysis of dependable systems by mapping fault trees into Bayesian networks

TL;DR: It is shown that any FT can be directly mapped into a BN and that basic inference techniques on the latter may be used to obtain classical parameters computed from the former, i.e. reliability of the Top Event or of any sub-system, criticality of components, etc.
Book

Introduction to reliability engineering

Elmer E Lewis
TL;DR: Reliability and Rates of Failure, Loads, Capacity, and Reliability, and System Safety Analysis; Quality and Its Measures; and Answers to Odd--Numbered Exercises.
Journal ArticleDOI

Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas

TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.
Book

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

TL;DR: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks.
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