A method for risk-informed safety significance categorization using the analytic hierarchy process and bayesian belief networks

Ha, Jun; Seong, Poong Hyun

doi:10.1016/j.ress.2003.08.002

Cited by 39 publications

(11 citation statements)

References 8 publications

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“…It is in this step where the conditional probability of one causal factor given the presence of other factor(s) is estimated using the "beliefs" of subject matter experts. While BBNs have also been combined with the Analytic Hierarchy Process (AHP) (Ha & Seong, 2004, Ahmed et al, 2005Park, et al, 2014) to assist in the probability quantification of accident precursors in some cases, the AHP is not used in this initial UAS geofencing study due to resource constraints. The gathering of the AHP data presents another elicitation burden and only offers an indirect method of obtaining the desired conditional probabilities.…”

Section: Methodology Building a Bayesian Belief Network (Bbn)mentioning

confidence: 99%

System Safety Modeling of Alternative Geofencing Configurations for small UAS

Luxhøj¹

2016

IJAAA

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Section: Methodology Building a Bayesian Belief Network (Bbn)mentioning

confidence: 99%

System Safety Modeling of Alternative Geofencing Configurations for small UAS

Luxhøj¹

2016

IJAAA

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“…New applications integrate AHP with other methods as mathematical programming techniques like, Data Envelopment Analysis, Fuzzy Sets, House of Quality, Genetic Algorithms, Neural Networks, SWOT-analysis (Ho and Emrouznejad, 2009). This trend is especially visible in the safety sector where AHP is combined with goal programming (Bertolini and Bevilacqua, 2006), MAUT (Karydas and Gifun, 2006), Bayesian analysis (Cagno et al, 2000;Carnero, 2006), Bayesian belief networks (Ha and Seong, 2004), (Ha and Seong, 2009). In this paper, we will describe in section 3.4, a new integration of AHP with CTA.…”

Section: Analytic Hierarchy Processmentioning

confidence: 99%

A hybrid and integrated approach to evaluate and prevent disasters

Ishizaka

Labib

2014

Journal of the Operational Research Society

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Disasters are, by their nature, very complex phenomena. Their modelling using a systematic and logical methodology can help us identify their root causes and may facilitate in allocating appropriate resources to prevent such situations. Although techniques exist to model such phenomena, a single off-the-shelf model is insufficient to provide an effective and realistic analysis to prevent disasters due to its inherent assumptions. In order to overcome these limitations of single methods, this article proposes a hybrid model of four methods to optimise a safety investment. First, a hierarchy is constructed with a problem structuring approach. Second, a new graphical representation, the Crisis Tree Analysis, is introduced to visualise how a combination of basic events may lead to a disaster. Third, the criticality of each event is assessed using the Analytic Hierarchy Process. Finally, a mathematical programming model is proposed to calculate the optimal allocation of available funds in order to avoid the disaster. A case study of the Bhopal disaster is used to illustrate the proposed four-step method.

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“…11. The AHP has been successfully applied in real applications; for example in software selection [24], information selection [25], manufacturing technology [26], supplier selection [27,28], risk-informed safety significance categorization [29], forecasting [23], and project evaluation [30]. In reference [31] it is applied to select a machine tool.…”

Section: Electre (Elimination Et Choix Traduisant La Realite)mentioning

confidence: 99%

Selection of condition monitoring techniques using discrete probability distributions: A case study

Carnero

2008

Proceedings of the Institution of Mechanical Engineers, Part O:

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The setting up of a condition monitoring program is considered a strategic decision owing to its influence on cost, safety, quality, and availability in an industrial plant. However, no previous structured analysis of the selection of condition monitoring techniques and their characteristics has been made, so further analysis is needed. This paper proposes a model for the selection of the most suitable condition monitoring technique to be set up in a subsidiary of a petrochemical plant. For this purpose, different criteria, indicators, and utility functions are defined; nine alternatives are proposed depending on the technological level of the condition monitoring program. The model applies the analytic hierarchy process to obtain a ranking of alternatives. Owing to the special characteristics of the decision, discrete probability distributions are defined. The final ranking is computed by applying the Monte Carlo method considering 2000 simulation trials. Finally, a sensitivity analysis is applied.

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A method for risk-informed safety significance categorization using the analytic hierarchy process and bayesian belief networks

Cited by 39 publications

References 8 publications

System Safety Modeling of Alternative Geofencing Configurations for small UAS

System Safety Modeling of Alternative Geofencing Configurations for small UAS

A hybrid and integrated approach to evaluate and prevent disasters

Selection of condition monitoring techniques using discrete probability distributions: A case study

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