MatCarloRe: An integrated FT and Monte Carlo Simulink tool for the reliability assessment of dynamic fault tree

Manno, Gabriele; Chiacchio, Francesco; Compagno, Lucio; D’Urso, Diego; Trapani, Natalia

doi:10.1016/j.eswa.2011.12.020

Cited by 63 publications

(39 citation statements)

References 33 publications

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“…The resolution of a DFT is much different than the one of the SFT, because temporal and cross dependencies cannot be modelled and solved through Boolean algebra [17].…”

Section: Dynamic Fault Tree Construction Methodsmentioning

confidence: 99%

DFT analysis of Ship pilotage risk based on A.D. Hall models

Wei

2017

MATEC Web Conf.

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Abstract. Based on A pilot station more than 10 years of pilotage safety accident database, from three angles, including time, link and space, the statistical of ship pilotage safety accident risk is analysis, from which obtain the pilotage safety accident characteristics, and provide the basic data for the risk assessment and risk analysis model. By using the improved A.D. Hall model, based on the study of accident database, a 3D model of ship pilotage risk assessment is established, which is from the time dimension, logic and resource dimension angle. From the point of view of resource dimension, the dynamic fault tree model is established considering the dynamic relationship between events, and the model is analysed by dynamic fault tree analysis (DFT). Based on the analysis results, measures to reduce pilotage risk are proposed.

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“…The resolution of a DFT is much different than the one of the SFT, because temporal and cross dependencies cannot be modelled and solved through Boolean algebra [17].…”

Section: Dynamic Fault Tree Construction Methodsmentioning

confidence: 99%

DFT analysis of Ship pilotage risk based on A.D. Hall models

Wei

2017

MATEC Web Conf.

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“…They are used particularly for analyzing DFT models to perform dynamic reliability assessment [48,49]. They mainly employ Monte Carlo simulation with the aim of overcoming the limitations of analytical methods such as state space explosion and lack of modularity in analysis [47]. There also exist studies that benefit from Bayesian Network (BN) that is a powerful method for probabilistic reasoning, particularly taking into account the complex dependencies in components and uncertainty in modeling.…”

Section: Related Workmentioning

confidence: 99%

“…These models are usually derived based on fault trees [16,46] that are provided as input. As an alternative approach to analytical resolution, there also exist simulation techniques and tools [47] applied on fault tree models. They are used particularly for analyzing DFT models to perform dynamic reliability assessment [48,49].…”

Section: Related Workmentioning

confidence: 99%

Identifying critical architectural components with spectral analysis of fault trees

Ayav

Szer

2016

Applied Soft Computing

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a b s t r a c tWe increasingly rely on software-intensive embedded systems. Increasing size and complexity of these hardware/software systems makes it necessary to evaluate reliability at the system architecture level. One aspect of this evaluation is sensitivity analysis, which aims at identifying critical components of the architecture. These are the components of which unreliability contributes the most to the unreliability of the system. In this paper, we propose a novel approach for sensitivity analysis based on spectral analysis of fault trees. We show that measures obtained with our approach are both consistent and complementary with respect to the recognized metrics in the literature.

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“…One of the main disadvantages of the use of simulation is the high effort that it requires for making the system model and data preparation (Kawauchi and Rausand, 1999). To this regard, new approaches are introducing the use of some conventional modeling techniques such as RBD or FTA for simulation purposes (Macchi et al, 2012;Manno et al, 2012;Roda et al, 2013). In fact the RBD logic has the advantages of giving a systemic, integrated and very compact view of the system with a bottom-up perspective, while keeping an easy implementation approach.…”

Section: Fig 13 Tools For the Performance Evaluation Modelmentioning

confidence: 99%

Application of a Performance-driven Total Cost of Ownership (TCO) Evaluation Model for Physical Asset Management

Roda

Garetti

2015

Lecture Notes in Mechanical Engineering

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The core concept of this paper is the total cost of ownership (TCO) of industrial asset and its relevance in supporting decision making if properly evaluated through the analysis of the asset technical performances. The paper is based on a framework that systematizes the benefits and potential applications of a TCO for different kind of stakeholders at different stages of the life cycle of the asset and for supporting different kind of decisions. The aim is to present an experimental case study that has been implemented to show the empirical evidence of what is in the framework by focusing on one of the primary companies in the chemical industry in Italy. The application proposes a modeling approach for trying to overcome one main relevant gap that still exists when referring to TCO models that is that most of the existing ones lack of the integration of technical performances evaluations into the cost models or are based on very limiting hypothesis. In this paper a comprehensive methodology for the evaluation of the Total Cost of Ownership of industrial assets that has being developed within a research activity carried out at the Department of Management, Economics and Industrial Engineering of Politecnico di Milano is presented. The objective of the proposed approach is to overcome the above mentioned limitations that are among the main obstacles for a spread application and use of TCO models in decision making for asset management.

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MatCarloRe: An integrated FT and Monte Carlo Simulink tool for the reliability assessment of dynamic fault tree

Cited by 63 publications

References 33 publications

DFT analysis of Ship pilotage risk based on A.D. Hall models

DFT analysis of Ship pilotage risk based on A.D. Hall models

Identifying critical architectural components with spectral analysis of fault trees

Application of a Performance-driven Total Cost of Ownership (TCO) Evaluation Model for Physical Asset Management

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