A comparison of accident analysis techniques for safety-critical man–machine systems

Kontogiannis, Tom; Leopoulos, Vrassidas; Marmaras, Nikos

doi:10.1016/s0169-8141(99)00022-0

Cited by 52 publications

(26 citation statements)

References 9 publications

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“…A traditional approach to learning from incidents is that when an analysis is performed with care and lessons are formulated, this will lead to the prevention of incidents [6,12,13,14]. However, learning from incidents should not only focus on preventing recurrence, but also on making an organisation inherently safer and on improving the learning from incidents process itself.…”

Section: Introductionmentioning

confidence: 99%

Critical Steps in Learning From Incidents: Using Learning Potential in the Process From Reporting an Incident to Accident Prevention

Drupsteen¹,

Groeneweg

Zwetsloot

2013

International Journal of Occupational Safety and Ergonomics

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Many incidents have occurred because organisations have failed to learn from lessons of the past. This means that there is room for improvement in the way organisations analyse incidents, generate measures to remedy identified weaknesses and prevent reoccurrence: the learning from incidents process. To improve that process, it is necessary to gain insight into the steps of this process and to identify factors that hinder learning (bottlenecks). This paper presents a model that enables organisations to analyse the steps in a learning from incidents process and to identify the bottlenecks. The study describes how this model is used in a survey and in 3 exploraorganisational learning incident survey learning potential case studies

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Section: Introductionmentioning

confidence: 99%

Critical Steps in Learning From Incidents: Using Learning Potential in the Process From Reporting an Incident to Accident Prevention

Drupsteen¹,

Groeneweg

Zwetsloot

2013

International Journal of Occupational Safety and Ergonomics

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“…Accident analysis techniques should provide appropriate input to others investigating complementary aspects of the system (Kontogiannis et al, 2000), combining different methodologies to better understand the problem in terms of human or casual factors. One of the most common mistakes during a risk analysis process is starting to consider the human behaviour as root cause for failures, violations and unsafe actions (even though most of the times it is the easiest and fast solution to identify the problem).…”

Section: The Accident Analysis Technique: a Post-event Investigation mentioning

confidence: 99%

Beyond Accidents: A Back-Analysis on Conveyor Belt Injury for a Better Design for Maintenance Operations

Martinetti¹,

Dongen²,

Romano³

2017

American Journal of Applied Sciences

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The conveyor belt represents one of the most commonly used methods of transporting bulk materials today. As highlighted multiple times in research, the moving parts are a critical issue causing accidents and injuries and several of these are strictly related to the opportunity to enter in working zones during maintenance activities, considered high-risk activity due to the nature of the job. For these reasons, maintenance operations have to be carefully planned during the design phase, with the adoption of appropriate safety measures for the maintenance crew and other people present in the area. On the other hand, preventative measures have to be put in action for maintenance operations and daily work. Analysing the accident reports related to the crushing and milling plants obtained from the several data bases and identifying with a Cause-Consequences analysis the root causes of an injury occurred in an Italian quarry, the paper underlines critical issues of the conveyor belts during maintenance operations, identifies common errors in the system management that affect the workers' safety and proposes an approach in order to improve the maintainability and the safety during the design phase.

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“…Risk value can be calculated as the product of the severity of the consequences that arise from the materialization of the RFs and the probability of the occurrence of RFs. In the literature, a few procedures have been proposed for the analysis of the potential consequences, such as fault trees and Petri Nets [27]. The severities of consequences assessment, for the situations where the consequences do not result in fatal injuries, can be performed in different ways.…”

Section: A Literature Reviewmentioning

confidence: 99%

ABC Classification of Risk Factors in Production Supply Chains with Uncertain Data

Vujović

Đorđević²,

Gojković

et al. 2017

Mathematical Problems in Engineering

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The problem of classification of risk factors in an uncertain environment is part of the risk management problem, which has a critical effect on the competitive advantage of production supply chain. The severities of consequences, their relative importance, and the frequency of occurrence of risk factors are defined by risk management team, depending on their experience and the results of good practice. Fuzzy rating of the severities of consequences and the frequency of occurrence of risk factors are described by linguistic expressions, which are modeled by triangular fuzzy numbers. The risk values, obtained by the materialization of the identified risk factors, are given precisely with the usage of fuzzy algebra rules. The classification criterion is defined as the distance between current risk value and extreme risk values. The proposed model enables determination of the priorities of risk factors. It is illustrated by an example with real-life data from a production supply chain in auto industry.

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A comparison of accident analysis techniques for safety-critical man–machine systems

Cited by 52 publications

References 9 publications

Critical Steps in Learning From Incidents: Using Learning Potential in the Process From Reporting an Incident to Accident Prevention

Critical Steps in Learning From Incidents: Using Learning Potential in the Process From Reporting an Incident to Accident Prevention

Beyond Accidents: A Back-Analysis on Conveyor Belt Injury for a Better Design for Maintenance Operations

ABC Classification of Risk Factors in Production Supply Chains with Uncertain Data

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