Affinity Diagram as a Risk Analysis Tool with Support of Fuzzy Logic

2013 ◽  
Vol 19 (8) ◽  
pp. 2391-2394
Author(s):  
E. Povolotskaya ◽  
P. Mach
Keyword(s):  
Fuzzy Logic ◽  
Risk Analysis ◽  
Analysis Tool

An operational risk analysis tool to analyze marine transportation in Arctic waters

2018 ◽  
Vol 169 ◽  
pp. 485-502 ◽  
Author(s):  
Bushra Khan ◽  
Faisal Khan ◽  
Brian Veitch ◽  
Ming Yang
Keyword(s):  
Risk Analysis ◽  
Operational Risk ◽  
Analysis Tool ◽  
Marine Transportation

Security of Railway Infrastructures

2012 ◽  
pp. 355-379
Author(s):  
A. Di Febbraro ◽  
F. Papa ◽  
N. Sacco
Keyword(s):  
Risk Analysis ◽  
Real World ◽  
Analysis Tool ◽  
Security Risk ◽  
Input Output ◽  
Real World Data ◽  
Security Problem ◽  
Output Characteristics ◽  
General Architecture

The chapter is organized as follows: In section 1, the basic definitions of the security risk analysis and the characteristics of the railway security problem are introduced, and a bibliography review is reported. Then, in section 2, the general architecture for designing a security risk analysis tool is presented, focusing on the relevant specifications, and on the input/output characteristics. Therefore, in section 3, with the aim of pointing out the characteristics of the presented architecture, an explicative case study is defined based on real world data coming from Italian railways. Finally, some conclusions and remarks are discussed in chapter 4.

Artificial intelligence treating the problem of uncertainty in quantitative risk analysis (QRA)

2019 ◽  
Vol 18 (1) ◽  
pp. 40-54
Author(s):  
Mohamed Seddik Hellas ◽  
Rachid Chaib ◽  
Ion Verzea
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Risk Analysis ◽  
Lung Damage ◽  
Whole Body ◽  
Individual Risk ◽  
Content Type ◽  
Quantitative Risk Analysis ◽  
Accident Scenario ◽  
Imperfect Knowledge

Purpose Nowadays, artificial intelligence computational methods, such as knowledge-based systems, neural networks, genetic algorithms and fuzzy logic, have been increasingly applied to several industrial research studies, the purpose of this paper is to study the contribution of fuzzy and possibilistic techniques to quantitative risk analysis (QRA) in the presence of imperfect knowledge about the occurrence and consequences of accidental phenomena. Design/methodology/approach To solve the problem of uncertainties related to the elements of the accident scenario such as the frequency and severity of the consequences, the authors used fuzzy logic. Using this type of analysis, it is possible to visualize the contours of the dead or fuzzy injury by fireball thermal effect (first- and second-degree burn, death) and lesions caused by vapor cloud explosion overpressure (lung damage, eardrum rupture, head impact, whole-body displacement). The frequency and severity of fuzzy results are calculated by extended multiplication using the alpha-cuts method. Findings This research project aims to reflect the real situation in the in Amenas industrial area (SONATRACH company), specifically the liquefied petroleum gas storage tank On-Spec 05-V-411A, to deal with this type of risk. Using this analysis allows us to estimate the fuzzy individual risk using the approach of fuzzy logic to treating this uncertainty in the parameter information of accident scenarios. This index individuel risk (IR) was evaluated against the criterion of acceptability and then used for decision-making in the field of industrial risk analysis and evaluation. Originality/value The originality of the work is to identify the weak points of the classical QRA to solve the problem of the uncertainties related to the elements of the accident scenario such as the frequency and severity of the consequences to visualize the fuzzy risk contours. On the one hand and the development of software to calculate the probability of death by the overpressure effect and classify the most sensitive organs on the other hand. Given the importance of this study, it can be generalized for similar sites in the region.

An invasive ant distribution database to support biosecurity risk analysis in the Pacific

2017 ◽  
Vol 23 (3) ◽  
pp. 258 ◽  
Author(s):  
Monica A. M. Gruber ◽  
Meghan Cooling ◽  
Allan R. Burne
Keyword(s):  
Invasive Species ◽  
Risk Analysis ◽  
Native Species ◽  
Small Island ◽  
Accurate Information ◽  
Analysis Tool ◽  
Invasive Ants ◽  
Invasive Ant ◽  
Conflicting Information ◽  
The Pacific

Invasive species are one of the most serious threats to biodiversity. Up-to-date and accurate information on the distribution of invasive species is an important biosecurity risk analysis tool. Several databases are available to determine the distributions of invasive and native species. However, keeping this information current is a real challenge. Ants are among the most widespread invasive species. Five species of ants are listed in the IUCN list of damaging invasive species, and many other species are also invasive in the Pacific. We sought to determine and update the distribution information for the 18 most problematic invasive ant species in the Pacific to assist Small Island Developing States with risk analysis. We compared the information on six public databases, conducted a literature review, and contacted experts on invasive ants in the Pacific region to resolve conflicting information. While most public records were accurate we found some new records had not yet been incorporated in the public databases, and some information was inaccurate. The maintenance of public databases faces an enormous challenge in balancing completeness (~15 000 ant species in this case) with accuracy (the impossibility of constantly surveying) and utility.

Applications of Fuzzy Logic

2017 ◽  
Author(s):  
Radim Bělohlávek ◽  
Joseph W. Dauben ◽  
George J. Klir
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Fuzzy Logic ◽  
Image Analysis ◽  
Quantum Mechanics ◽  
Risk Analysis ◽  
Current Status ◽  
Application Domain ◽  
Business Decision ◽  
And Mathematics

The high visibility of fuzzy logic and mathematics based on fuzzy logic is primarily due to their highly successful applications in many areas of human affairs. The aim of this chapter is to characterize the evolution and current status of these applications. Covered are applications in the various areas of engineering, natural, social and earth sciences, psychology, medicine, management and business, decision making, pattern recognition, image analysis, risk analysis, music, among others. In each of these areas, the significance of using fuzzy logic and the associated mathematics is critically assessed. It is argued that in some application areas, such as psychology or quantum mechanics, a cooperation between researchers in fuzzy logic and those in the application domain, leading possibly to new types of nonstandard fuzzy sets, is essential for further progress.

Atmospheric metal pollutants and environmental injustice: A methodological approach to environmental risk analysis using fuzzy logic and tree bark

2016 ◽  
Vol 71 ◽  
pp. 428-437 ◽  
Author(s):  
Bruno Martins Gurgatz ◽  
Regiani Carvalho-Oliveira ◽  
Daniel Canavese de Oliveira ◽  
Emerson Joucoski ◽  
Gisele Antoniaconi ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Risk Analysis ◽  
Environmental Risk ◽  
Methodological Approach ◽  
Tree Bark ◽  
Environmental Injustice ◽  
Metal Pollutants ◽  
Environmental Risk Analysis

Identifying Risk at the Conceptual Phase of Product Design: A Software Solution

2007 ◽  
Author(s):  
Karthik Sundaram ◽  
Abhishek Chakravarty ◽  
Katie Grantham Lough ◽  
Derek Ditch
Keyword(s):  
User Interface ◽  
Risk Analysis ◽  
Software Architecture ◽  
Product Design ◽  
Design Process ◽  
Graphical User Interface ◽  
Analysis Tool ◽  
University Of Missouri ◽  
Early Design ◽  
Design Software

This paper introduces RED (Risk in Early Design) software developed by the R.I.S.K by Design Lab at University of Missouri-Rolla. The RED software is a risk analysis tool that enables failure prevention to begin during the conceptual phase of product design. The main focus of the paper is describing the software architecture and application. Its unique graphical user interface allows designers to simply select the functions of the system being designed and the software immediately generates a risk analysis report. This analysis categorizes risk likelihood and consequence elements for a product by translating the recorded information about function and failure. An example describing the software’s use in the design process is also presented.

STP Balance of Plant Model Update Experience and Results

2009 ◽  
Author(s):  
Ernie Kee ◽  
Fatma Yilmaz ◽  
Don Wakefield ◽  
Steve Epstein
Keyword(s):  
Risk Analysis ◽  
Fault Tree ◽  
Assessment Model ◽  
Analysis Tool ◽  
Event Tree ◽  
Data Types ◽  
Model Framework ◽  
Production Risk ◽  
Balance Of Plant ◽  
Production Losses

The South Texas Project (STP) balance of plant (BOP) model for production losses has been converted from an Excel-based software application that uses minimal cutsets from a single large fault tree, to a set of small fault trees used within a risk analysis tool, Riskman® [8]. The Riskman® application provides estimates of interest to plant investors and owners such as potential production losses and plant profitability, as well as production reliability and quality (loss frequency, type of loss, loss duration and standard economic risk metrics). The BOP models and methodologies developed are applicable to both fault-tree linking and event-tree linking styles of risk analysis. The STP BOP model is developed to support configuration risk management in two categories: 1) trip risk and concomitant core damage frequency; and 2) non-trip production risk. The primary purpose for the conversion work is to make the STP BOP model framework and application platform consistent with the STP probabilistic risk assessment model. In the course of the conversion, improvements to the Riskman® software have been implemented and techniques to more efficiently produce BOP modeling (fault tree) improvements were developed. Better methods to accurately calculate initiating event frequencies are studied. New data types added to support BOP modeling are described.

Sign in / Sign up

Export Citation Format

Share Document