This document summarizes and compares two journal articles on accident modeling approaches. The first article by Hollnagel describes general modeling approaches like sequential, epidemiological, and systemic models. It also discusses the role of humans in accidents in terms of their actions and work mentality. The second article by Sklet compares 14 accident investigation methods based on criteria like graphical representation, safety barriers focus, and required expertise. Both articles highlight the importance of using multiple modeling approaches and accounting for human factors when investigating accidents.
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Book report on "A Human Error Approach to Aviation Accident Analysis" by Douglas Wiegmann and Scott Schappell for Purdue University graduate course AT 573 Managing the Risks of Organizational Accidents.
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CITE PhD Student research Seminar Presentation at the University of East London
Speaker: Amin Hosseinian Far
Title: Artificial Intelligence Techniques for Modelling Systems’ Sustainability : A Review
MOS 6625, System Safety Engineering 1 Course Learning .docxgilpinleeanna
MOS 6625, System Safety Engineering 1
Course Learning Outcomes for Unit IV
Upon completion of this unit, students should be able to:
2. Analyze public policy issues with consideration given to societal norms and preferences related to
engineering systems.
2.1 Demonstrate an understanding of how systems theory can be utilized in contemporary accident
causation models to accomplish the intended outcomes underpinning Occupational Safety and
Health Administration (OSHA) regulatory compliance management within the industrial sector.
2.2 Demonstrate an understanding of how the STAMP model of accident causation compares to
other contemporary systems-based accident causation models developed for the industrial
sector.
2.3 Demonstrate an understanding of global systems-based approaches at implementing accident
causation management systems within the industrial sector.
Reading Assignment
Chapter 4: A Systems-Theoretic View of Causality, pp. 77-100
Kwon, H., Yoon, H., & Moon, I. (2006). Industrial applications of accident causation management system.
Chemical Engineering Communications, 193(8), 1024-1037. doi:10.1080/00986440500352089
Mitropoulos, P., Abdelhamid, T., & Howell, G. (2005). Systems model of construction accident causation.
Journal of Construction Engineering and Management, 131(7), 816-825. doi: 10.1061/(ASCE)0733-
9364(2005)131:7(816)
Unit Lesson
In Unit II and Unit III, we closely considered Leveson’s (2011) STAMP model in various applications related to
a wide cross-section of industry sectors. Specifically, we considered the three major components of a cost-
effective system safety process (including the subsystems of management, development, and operations
within the larger system). As such, we recall that this design effectively incorporates the most powerful design
features known to optimize the decision-making process. Further, we recall that the STAMP model works to
align and subsequently address processes and identify controls with a clear, linear perspective of systems
component criteria interrelationships. As such, we deduced that as scholar-practitioners of safety engineering
and decision science, we must become proficient practitioners at managing within various fields of
engineering disciplines.
In this unit, with the clear intent of preparing ourselves for your ultimate creation of an operations safety
management plan for a specific industry in Unit VIII of this course, we now begin to analyze samples of
contemporary systems-based accident causation models against the STAMP model.
First, we want to consider the industry sectors that were at the heart of the establishment of the Occupational
Safety and Health Administration (OSHA), given that this might lend us the information that we need to
closely pair OSHA’s intentions for a safer workplace with our own interest in mitigating accidents. We must
remember that the sole purpose of OSHA is to protect workers as they go about th ...
A Novel Approach to Derive the Average-Case Behavior of Distributed Embedded ...ijccmsjournal
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research work, we have put an emphasis on reliability assessment of any distributed embedded system
through Monte-Carlo simulation. We have done this assessment on random data which represents input
voltages ranging from 0 volt to 12 volt; several numbers of trials have been executed on those data to
check the average case behavior of a distributed real time embedded system. From the experimental result, a saturation point has been achieved against the time behavior which shows the average case behavior of the concerned distributed embedded system.
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Exploring the advantage of simulation research- Insights from Feliz ozel. As a part of the Architectural Research Methods by Linda N. Groat, David Wang
Exploring the World of Models-A Comprehensive GuideMuhammad Hashim
Explore the intricate world of models with our latest article! Discover how these powerful tools impact fields like engineering, medicine, and economics. Learn about different types of models, their applications, and the future trends shaping modeling. Dive in now to unlock insights and predictions!
CITE PhD Student research Seminar Presentation at the University of East London
Speaker: Amin Hosseinian Far
Title: Artificial Intelligence Techniques for Modelling Systems’ Sustainability : A Review
MOS 6625, System Safety Engineering 1 Course Learning .docxgilpinleeanna
MOS 6625, System Safety Engineering 1
Course Learning Outcomes for Unit IV
Upon completion of this unit, students should be able to:
2. Analyze public policy issues with consideration given to societal norms and preferences related to
engineering systems.
2.1 Demonstrate an understanding of how systems theory can be utilized in contemporary accident
causation models to accomplish the intended outcomes underpinning Occupational Safety and
Health Administration (OSHA) regulatory compliance management within the industrial sector.
2.2 Demonstrate an understanding of how the STAMP model of accident causation compares to
other contemporary systems-based accident causation models developed for the industrial
sector.
2.3 Demonstrate an understanding of global systems-based approaches at implementing accident
causation management systems within the industrial sector.
Reading Assignment
Chapter 4: A Systems-Theoretic View of Causality, pp. 77-100
Kwon, H., Yoon, H., & Moon, I. (2006). Industrial applications of accident causation management system.
Chemical Engineering Communications, 193(8), 1024-1037. doi:10.1080/00986440500352089
Mitropoulos, P., Abdelhamid, T., & Howell, G. (2005). Systems model of construction accident causation.
Journal of Construction Engineering and Management, 131(7), 816-825. doi: 10.1061/(ASCE)0733-
9364(2005)131:7(816)
Unit Lesson
In Unit II and Unit III, we closely considered Leveson’s (2011) STAMP model in various applications related to
a wide cross-section of industry sectors. Specifically, we considered the three major components of a cost-
effective system safety process (including the subsystems of management, development, and operations
within the larger system). As such, we recall that this design effectively incorporates the most powerful design
features known to optimize the decision-making process. Further, we recall that the STAMP model works to
align and subsequently address processes and identify controls with a clear, linear perspective of systems
component criteria interrelationships. As such, we deduced that as scholar-practitioners of safety engineering
and decision science, we must become proficient practitioners at managing within various fields of
engineering disciplines.
In this unit, with the clear intent of preparing ourselves for your ultimate creation of an operations safety
management plan for a specific industry in Unit VIII of this course, we now begin to analyze samples of
contemporary systems-based accident causation models against the STAMP model.
First, we want to consider the industry sectors that were at the heart of the establishment of the Occupational
Safety and Health Administration (OSHA), given that this might lend us the information that we need to
closely pair OSHA’s intentions for a safer workplace with our own interest in mitigating accidents. We must
remember that the sole purpose of OSHA is to protect workers as they go about th ...
A Novel Approach to Derive the Average-Case Behavior of Distributed Embedded ...ijccmsjournal
Monte-Carlo simulation is widely used in distributed embedded system in our present era. In this
research work, we have put an emphasis on reliability assessment of any distributed embedded system
through Monte-Carlo simulation. We have done this assessment on random data which represents input
voltages ranging from 0 volt to 12 volt; several numbers of trials have been executed on those data to
check the average case behavior of a distributed real time embedded system. From the experimental result, a saturation point has been achieved against the time behavior which shows the average case behavior of the concerned distributed embedded system.
Rogers Revised Presentation For Cali WorkshopPatriciaJRogers
Presentation to "Rethinking Impact: Understanding theComplexity of Poverty and Change", 26 - 28 March 2008Cali, Colombia. It oulined four key tasks for impact evaluation and sets out some methods that can be used for each of these.
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2. TASK
To summarize a discuss the following journal articles and
conference proceedings.
Papers compare accident modeling approaches in
varying degrees of detail.
Understanding Accidents - From Root Causes to
Performance Variability
(Hollnagel, 2002)
Comparison of some selected methods for accident
investigation
(Sklet, 2003)
4. BACKGROUND
Published in 2002 in the Proceedings of the 2002 IEEE 7th
Conference on Human Factors and Power Plants.
Erik Hollnagel
Department of Computer and Information Science, University of Linkoping, Sweden
Accidents Analysis and Accident Prevention
The variability of Human Performance
Modelling of Cognition
Developed FRAM and CREAM
5. AIM
To give an overview of the developments in accident
modeling.
How these developments have effected accident
analysis and prevention.
1. Summary and analysis of the general modeling
approaches (Sequential, Epidemiological, Systemic).
2. The role of humans in the accident process(actions of
humans, work mentally of humans).
6. STRUCTURE
Summary of modeling techniques
- Sequential
- Epidemiological
- Systemic
Comparison of approaches
Role of Humans in accidents
- actions of humans
- work mentality of humans
Conclusion
8. DOMINO MODEL OF
ACCIDENT CAUSATION
(Ferry, 1988)
5 factors in the accident sequence
1. Social environment
Factors effect an individuals perception of risk
2. Fault of the person
Human error
3. Unsafe acts or environment
faulty equipment, hazards in the environment
4. Accident
5. Injury
10. ACCIDENT EVOLUTION
AND BARRIER MODEL
Accidents are represented as sequences of events or
barriers that failed.
Target what went wrong.
Leaves out other factors that may be import in the
investigation
(Øien, 2001)
11. SUMMARY OF
SEQUENTIAL APPROACH
Attractive:
Allows you to think in a casual sequence
Represent as a graph
Allows easy communication of findings
Limited:
Not powerful enough to model more complex systems.
12. GENERAL MODELING
APPROACHES -
EPIDEMIOLOGICAL
Accident is described as a disease.
Some factor that effects the accident occur right
away while others are latent.
Takes into account that events can manifest over time
Swiss cheese Model (Reason, 1997)
13. SUMMARY OF
EPIDEMIOLOGICAL
APPROACH
Overcome Limitations:
Superior to sequential models as latent events can be taken
into account.
More suited to modeling complex systems.
Lack of detail:
Allowed the idefaction of general events that occurred could
not go deeper.
14. SUMMARY OF
SYSTEMIC APPROACH
Accidents naturally emerge, they are expected to occur. As
detailed In Perrow’s Normal Accidents.
(Perrow, 1984)
Focus:
Systemic models focus on the characteristics of a systems
as oppose to a series of events that cause the accident in the
system.
Difficult but powerful:
Ideal for complex systems but hard to represent graphically.
15. COMPARISON OF
APPROACHES
Table comparing
general approaches
Highlights:
1. What the accident
model produces
1. How the product
information can be
used in accident
prevention
(Hollnagel, 2002)
16. COMPARISON OF
APPROACHES
Sequential models – search for root-cause of event
- event linked by cause effect
- cause is found then accident is prevented.
Epidemiological models – Looks at factors that may manifest
later
- Looks at barriers that can be re-
enforced or created to prevent further
accident
Systemic models – looks for unusual relationships.
- Monitors variability in systems performance
- Variability can be good and bad allows the
system to develop, but bad variably must be
trapped.
17. COMPARISON OF
APPROACHES-
CONCLUSION No one modeling
approach is better
. than the other.
Each modeling
approach has its
own strengths
These models should
be used in conjunction
with each other for the
best results.
18. ROLE OF HUMANS IN
ACCIDENTS
Humans play a role a ever level in an accident not just the
sharp end.
Everyone blunt end is someone else's sharp end.
Blunt end sharp end relationship (Hollnagel, 2002)
19. ACTIONS OF HUMANS
Humans actions are not black
and white and can only be judge
in hindsight.
People do what they think
is right at the time.
Different degrees of ‘being right’
not just correct or fail.
(Amalberti, 1996)
21. ACTIONS OF HUMANS
In the sequential model an element is either correct or has
failed, but human actions are not like this
Human actions are better suited to the epidemiological model
as it allows for latent conditions , it takes into account that action
may contribute to accident over time.
The systemic model is built on the concept of variability and
does not focus on failures. This is perfect for representing
variability of human action.
22. WORK MENTALITY OF
HUMANS
Efficiency-Thoroughness Trade-off (ETTO) Principle
(Hollnagel, 2002)
Human performance must satisfy conflicting criteria.
Will try and meet task demand and be as thorough as
believed necessary while still being as efficient as
possible and not wasting effort.
Performance can only increase in a stable environment
RO-RO ferries
Normal performance
23. CONCLUSION
“Normal performance and failures are emergent phenomena”
(Hollnagel, 2002)
Neither can be attributed to a specific part of function
of the system.
The adaptability of human work is the reason behind its
efficacy and it failures.
24. COMPARISON OF SOME SELECTED METHODS
FOR ACCIDENT INVESTIGATION
(Sklet, 2004)
25. BACKGROUND
Published in 2003 in Journal of Hazardous Materials
Snorre Sklet
Department of Production and Quality Engineering Norwegian University of Science and
Technology, Norway
Risk Analysis and Risk Influence Modeling
Safety Barriers
Safety Management
Accident Investigation
Does a lot of work with the oil industry
26. AIM
To give a brief summary of highly recognized accident
investigation methods developed over last decade .
To compare these selected methods to highlight there
qualities and deficiencies.
1. Summary of the methods ) brief summary of each one,
framework for comparison).
2. Comparison of methods(table, analysis of comparison).
28. SELECTED METHODS
Events and causal factors charting and analysis.
Barrier analysis.
Change analysis.
Root cause analysis.
Fault tree analysis.
Influence diagram.
Event tree analysis.
Management and Oversight Risk Tree (MORT).
Systematic Cause Analysis Technique (SCAT).
Sequential Timed Events Plotting (STEP).
Man, Technology and Organisation (MTO)-analysis.
The Accident Evolution and Barrier Function (AEB) method.
TRIPOD.
Acci-Map.
No systemic methods compered
29. FRAMEWORK OF
COMPARISON
Details Framework of comparison highlighting the strengths
and weakness of each technique.
7 categories
Whether the methods give a graphical description of the event sequence
or not?
Can give overview of events
Allows for clear communication
Easy to see broken link
To what degree the methods focus on safety barriers?
Analysis of protective elements in the the system
30. FRAMEWORK OF
COMPARISON
The level of scope of the analysis.
Which levels of Rasmussen’s classification of
sociotechnical systems (Rasmussen, 1997) does the
method model.
(Rasmussen, 1997)
31. FRAMEWORK OF
COMPARISON
What kind of accident models that has influenced the methods?
sequential model, epidemiological model, systemic model
Whether the different methods are inductive, deductive,
morphological or non-system-oriented?
The way in which the method looks at the accident e.g.
does reason from the general to the specific.
32. FRAMEWORK OF
COMPARISON
Whether the different methods are primary or secondary
methods?
Primary Method – Self contained, stand alone method.
Secondary Method – used in conjunction with other
method to provide special input.
The need for education and training in order to use the methods.
Novice – no experience or training is needed.
Specialist – In between Novice and expert.
Expert – Formal education and training is needed.
34. ANALYSIS OF THE
COMPARISON
The strongest in terms of graphical representation is STEP
as it does not use a single axis and can represent one – one
or one - *
Scope of most methods focus on levels 1-4 of the
sociotechnical systems
Identifying the casual factors or event paths is important.
35. CONCLUSION
Accidents do not have a single cause so the investigation
should reflected this buy using multiple methods.
A graphical representation is key, as it allows easy
communication of information.
There should be one person of every investigation team that
has the knowledge of different accident modeling techniques
so the right tools can be chosen for the job
36. REFERENCES
Amalberti, R. (1996). La conduite des systkmes ri risques. Paris: PUF.
Department of Energy. (1999). DOE Workbook, Conducting Accident Investigations . Washington,: Department
of Energy.
Ferry, T. (1988). Modern Accident Investigation and Analysis. Second Edition. New York: Wiley.
Høyland, A., & Rausand, M. (1994). System reliability Theory: Models and Statistical Methods. New York: Wiley.
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Editor's Notes
Functional Resonance Accident ModelCognitive Reliability and Error Analysis Method
Functional Resonance Accident ModelCognitive Reliability and Error Analysis Method