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.About:
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.read more
Citations
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Book ChapterDOI
Fault Tree and Bayesian Network Based Scraper Conveyer Fault Diagnosis
TL;DR: The fault tree of coal mining compressors is obtained by means of artificial deduction, and the reliability of scraper conveyor was obtained by Bayesian networks and fault trees and the occurrence rate of the fault.
Proceedings ArticleDOI
A flexible and concise framework for hazard quantification
TL;DR: A general framework to compute limiting tolerable hazard rate (LTHR) in complex railway system and motivates the investigation of using Bayesian Networks (BNs) for functional safety analysis of DMI.
Journal ArticleDOI
A bayesian network-based approach for failure analysis in weapon industry
TL;DR: A Bayesian Network (BN)based modeling approach is employed for capturing dependency among the basic events and obtaining top event probability in a fault tree analysis of a leading weapon factory in Turkey.
Journal ArticleDOI
A fuzzy-HAZOP/ant colony system methodology to identify combined fire, explosion, and toxic release risk in the process industries
TL;DR: In this paper , a hybrid approach that merges a fuzzy HAzard and OPerability (fuzzy-HAZOP) technique, an Ant Colony System (ACS), and fuzzy set theory was introduced to evaluate the coupling of fire, explosion, and toxic release risk in the process industries.
Journal ArticleDOI
Multi-hazard risk assessment in process industries: State-of-the-Art
Zhichao He,Chao Chen,Wenguo Weng +2 more
TL;DR: In this paper, the authors reviewed past studies on the risk assessment of three types of multi-hazard accidents in process industries: Natech events, domino effects, and concurrent hazards.
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
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
Uffe Kjærulff,Anders L. Madsen +1 more
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.