This document provides an overview of four systemic accident modeling techniques: CREAM, FRAM, AcciMap, and STAMP. It discusses the background, key ideas, and methods for each technique. It also expands upon a framework for comparing accident modeling techniques, analyzing the techniques on factors like accident sequence consideration, safety barrier focus, analytical levels and approaches, and training needs.
it helps in investigate a problem,explore it and identify it easily.it is constructive by effort and attractive.
team members:-
nisha verma, nikita, shreya gupta.
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.
it helps in investigate a problem,explore it and identify it easily.it is constructive by effort and attractive.
team members:-
nisha verma, nikita, shreya gupta.
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.
Full paper presented at the NPRA National Safety Conference, 1999 in Dallas "Human Performance Engineering: A Practical Approach to Application of Human Factors. [Relevant to safe operation of "high hazard" facilities, for example in process and energy industries.]
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.
Engineering Ambient Intelligence Systems using Agent TechnologyNikolaos Spanoudakis
This presentation was given at the nectar session of the 9th Hellenic Conference on Artificial Intelligence (SETN 2016) that took place on May18th- 20th in Thessaloniki.
It is about applying an agent-oriented software engineering (AOSE) methodology, i.e. the Agent Systems Engineering Methodology (ASEME) for building intelligent systems. We present it along with a case study in the Ambient Intelligence (AmI) Application Domain. We discuss the challenges, the ASEME Methodology, the System Architecture and our results.
Development of Modified Evaluation and Prioritization of Risk Priority Number...CSCJournals
Failure Mode and Effects Analysis (FMEA) is a tool used for identifying, analyzing and prioritizing failure modes of a product and process. The traditional FMEA determines the risk priority of each failure mode using the risk priority number (RPN) by multiplying the ranks of the three risk factors namely the Severity (S), Occurrence (O) and Detection (D). FMEA is carried out by a team of members and the critical problem is that the team often demonstrates different opinions from one member to another. Then, there is a disagreement in ranking value for the three risk factors. In case average out of difference is considered, the different combination of three risk factors may produce an identical RPN value for different failure modes. In the present work, the modified RPN prioritization method is introduced into traditional FMEA to solve the above issue and this method is applied in the risk evaluation of water leakage in the building. Finally, the proposed method has been evaluated using statistical analysis techniques. The result indicates that the proposed method is useful for RPN evaluation and prioritization of failure modes.
Milestone One Company Identification You have been hired as a.docxARIV4
Milestone One: Company Identification
You have been hired as a consultant at the company you have been researching (APPLE INC.). This report is an in-depth look at the strategy and corporate management based on your detailed research completed throughout the semester.
Identify the company you are researching along with answers to the Component 1 assignment questions.
Company: Apple Inc.
Strategy and the Strategic Management Process at your Chosen Company
Describe the industry you are investigating. Identify the company you are researching along with the mission, vision, values, and strategic plan. Be sure to answer the following questions:
· Describe the industry in which the company operates.
· What is the company’s stated strategy? Is it a winning strategy?
· How does the company’s mission statement compare to those of its competitors?
· How do the mission, vision, and values support strategic objectives or performance targets of your company?
· What do the mission, vision, and value statements say about the company and its leadership?
APA format, with citation within the text and reference page (academic resources at least 2).
MOS 6625, System Safety Engineering 1
Course Learning Outcomes for Unit III
Upon completion of this unit, students should be able to:
3. Evaluate new approaches to safety based on modern systems thinking and theory.
3.1 Demonstrate an understanding of the Systems-Theoretic view of causality.
3.2 Demonstrate a working knowledge of the STAMP model of accident causation.
Reading Assignment
Chapter 6: Engineering and Operating Safer Systems Using STAMP
Chapter 7: Fundamentals
Unit Lesson
In the first two units, we learned about Deming’s (1986) engineering design for continuous improvement
(Plan-Do-Check-Act or PDCA cycle), and we learned about our role as scholar-practitioners of safety
engineering being firmly rooted as decision management scientists. Further, we were introduced to Leveson’s
(2011) STAMP (Systems-Theoretic Accident Model and Process) causality model, synthesized from
traditional safety engineering models of accident causation, and reengineered to a systems perspective.
In this unit, we are revisiting the STAMP model while learning to apply and deploy the STAMP in various other
applications related to a wide cross-section of industry sectors. One critical aspect of Leveson’s (2011)
STAMP model design is the careful incorporation of three major components of a cost-effective system safety
process. These include the subsystems of management, development, and operations within the larger
system. As such, this design effectively incorporates the most powerful design features known to optimize the
decision-making process, given that the STAMP model works to align and subsequently address processes. It
can then be used to identify controls with a clear, linear perspective of systems component criteria
interrelationships (see Figure 6.1). This means that as schol ...
Full paper presented at the NPRA National Safety Conference, 1999 in Dallas "Human Performance Engineering: A Practical Approach to Application of Human Factors. [Relevant to safe operation of "high hazard" facilities, for example in process and energy industries.]
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.
Engineering Ambient Intelligence Systems using Agent TechnologyNikolaos Spanoudakis
This presentation was given at the nectar session of the 9th Hellenic Conference on Artificial Intelligence (SETN 2016) that took place on May18th- 20th in Thessaloniki.
It is about applying an agent-oriented software engineering (AOSE) methodology, i.e. the Agent Systems Engineering Methodology (ASEME) for building intelligent systems. We present it along with a case study in the Ambient Intelligence (AmI) Application Domain. We discuss the challenges, the ASEME Methodology, the System Architecture and our results.
Development of Modified Evaluation and Prioritization of Risk Priority Number...CSCJournals
Failure Mode and Effects Analysis (FMEA) is a tool used for identifying, analyzing and prioritizing failure modes of a product and process. The traditional FMEA determines the risk priority of each failure mode using the risk priority number (RPN) by multiplying the ranks of the three risk factors namely the Severity (S), Occurrence (O) and Detection (D). FMEA is carried out by a team of members and the critical problem is that the team often demonstrates different opinions from one member to another. Then, there is a disagreement in ranking value for the three risk factors. In case average out of difference is considered, the different combination of three risk factors may produce an identical RPN value for different failure modes. In the present work, the modified RPN prioritization method is introduced into traditional FMEA to solve the above issue and this method is applied in the risk evaluation of water leakage in the building. Finally, the proposed method has been evaluated using statistical analysis techniques. The result indicates that the proposed method is useful for RPN evaluation and prioritization of failure modes.
Milestone One Company Identification You have been hired as a.docxARIV4
Milestone One: Company Identification
You have been hired as a consultant at the company you have been researching (APPLE INC.). This report is an in-depth look at the strategy and corporate management based on your detailed research completed throughout the semester.
Identify the company you are researching along with answers to the Component 1 assignment questions.
Company: Apple Inc.
Strategy and the Strategic Management Process at your Chosen Company
Describe the industry you are investigating. Identify the company you are researching along with the mission, vision, values, and strategic plan. Be sure to answer the following questions:
· Describe the industry in which the company operates.
· What is the company’s stated strategy? Is it a winning strategy?
· How does the company’s mission statement compare to those of its competitors?
· How do the mission, vision, and values support strategic objectives or performance targets of your company?
· What do the mission, vision, and value statements say about the company and its leadership?
APA format, with citation within the text and reference page (academic resources at least 2).
MOS 6625, System Safety Engineering 1
Course Learning Outcomes for Unit III
Upon completion of this unit, students should be able to:
3. Evaluate new approaches to safety based on modern systems thinking and theory.
3.1 Demonstrate an understanding of the Systems-Theoretic view of causality.
3.2 Demonstrate a working knowledge of the STAMP model of accident causation.
Reading Assignment
Chapter 6: Engineering and Operating Safer Systems Using STAMP
Chapter 7: Fundamentals
Unit Lesson
In the first two units, we learned about Deming’s (1986) engineering design for continuous improvement
(Plan-Do-Check-Act or PDCA cycle), and we learned about our role as scholar-practitioners of safety
engineering being firmly rooted as decision management scientists. Further, we were introduced to Leveson’s
(2011) STAMP (Systems-Theoretic Accident Model and Process) causality model, synthesized from
traditional safety engineering models of accident causation, and reengineered to a systems perspective.
In this unit, we are revisiting the STAMP model while learning to apply and deploy the STAMP in various other
applications related to a wide cross-section of industry sectors. One critical aspect of Leveson’s (2011)
STAMP model design is the careful incorporation of three major components of a cost-effective system safety
process. These include the subsystems of management, development, and operations within the larger
system. As such, this design effectively incorporates the most powerful design features known to optimize the
decision-making process, given that the STAMP model works to align and subsequently address processes. It
can then be used to identify controls with a clear, linear perspective of systems component criteria
interrelationships (see Figure 6.1). This means that as schol ...
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In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
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In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
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2. TASK
To give an overview of systemic modeling approaches
Discuss selected systemic accident modeling
techniques and the academic literature surrounding
them.
To expanded the frame work for comparing accident
modeling techniques set out in Comparison of some
selected methods for accident investigation
(Sklet, 2004)
To Compare selected techniques using the expanded
framework
3. SYSTEMIC APPROACH
Considers the performance of the system as a whole.
Organization
Environmental
Human
Technical
System is view as many components interacting causing a
equilibrium.
Systemic can evolve dynamically
Flawed interactions between components could cause
system to be thrown out of balance
Accident
4. METHODS REVIEWED
Cognitive Reliability Error Analysis Method (CREAM)
(Hollnagel E. , Cognitive Reliability and Error Analysis Method., 1998)
The Functional Resonance Analysis Method (FRAM)
(Hollnagel E. , FRAM – The Functional Resonance Analysis Method, 2012)
AcciMap
(Rasmussen, 1997)
Systems-Theoretic Accident Model and Processes (STAMP)
(Leveson, 2004)
5. CREAM - COGNITIVE
RELIABILITY AND ERROR
ANALYSIS METHOD
(Hollnagel E. , Cognitive Reliability and Error Analysis Method., 1998)
Background:
Developed by Erik Hollnagel in 1998
Cognitive system engineering approach
design of human-machine systems accounting for
factors of the environment in which the system
exists.
Key idea:
Cognitive modeling of human performance for accident
analysis or performance predictions
6. COGNITIVE SYSTEM
ENGINEERING
Technology has changed the way in which humans work
Manual tasks
Knowledge heavy(thinking) tasks.
Change has lead to new problems in human performance
causing new types of failures in sociotechnical systems.
Human reliability analysis context-dependent cognitive
reliability analysis.
Analysis of the probability of a person performing
a system required action in a given time with out an
activity that will be detrimental to the system being
performed.
7. SOLUTION - CREAM
AIM:
1. To identify components of the systems which relies on
human cognition
2. To find conditions under which cognition is reduced and
thus leading to failure state.
3. To evaluate human performance in the system and there
effect on the safety of the system can be used as part of
probability risk assessment(PRA).
4. To develop new components or to improve exciting
components to increase cognitive reliability and reduce
risk.
8. METHOD
Control modes:
Control mode Reliability interval
Degree Strategic 0.5 E-5 < p < 1.0 E-2
of Tactical 1.0 E-3 < p < 1.0 E-1
control Opportunistic 1.0 E-2 < p < 0.5 E-0
Scrambled 1.0 E-1 < p < 1.0 E-0
Reliability interval – The probability of action failures
9. METHOD
Common Performance
Conditions:
The minimum number of factors
that are vital in order to describe
the context of the system.
State of each CPC is assessed by
analyst
(Kim, Seong, & Hollnagel, 2006)
10. METHOD
Control mode determination:
CPC Score = (number of reduced, number of improved)
(Hollnagel E. , Cognitive Reliability and Error Analysis Method., 1998)
Operators performance is the accessed and improvements are recommended
11. FRAM - FUNCTIONAL
RESONANCE ANALYSIS
METHOD
(Hollnagel E. , FRAM – The Functional Resonance Analysis Method, 2012)
Background:
Developed by Erik Hollnagel in 2004
Performance variability
Performance in a system whither internal, external
dynamically fluctuates. Variability in complex systems is
normal.
Key idea:
Models how components of a system resonate and interact
with each other causing the system to lose balance leading
to accidents.
12. METHOD
1. Identify Vital system functions and categories functions
(Hollnagel E. , Functional Resonance Accident Model Method and examples, 2005)
13. METHOD
2. Describe potential variability of system.
3. Identify
functions that have
dependency that
may effect the
system
4. Identify barriers
for variability and
specify required
performance
monitoring
(Hollnagel E. , Functional Resonance Accident Model Method and examples, 2005)
14. ACCI-MAP
(Rasmussen, 1997)
Background:
Developed by J. Rasmussen and I. Svedung in 2000
Utilizes Rasmussen hierarchical model of socio-technical
systems
Key idea:
A model that describes an accident in terms of different
levels of socio-technical systems
16. METHOD
Cause-Consequence chart that extends across the
hierarchical levels. (Transportation of dangerous goods)
(Svedung & Rasmussen , 2002)
17. STAMP - SYSTEMS-THEORETIC
ACCIDENT MODEL AND
PROCESSES
(Leveson, 2004)
Background:
Developed by Nancy Leveson in 2004
System theory
Systems are self regulating, this is achieved through
feedback loops
Key idea:
Accidents do not occur as a result of individual component
failures. Accidents are a results of external forces and
dysfunctional interactions of components not being correctly
managed .
18. METHOD
1. Development of hierarchical control structure which
show the interactions between different system
components, safety regulations and constraints.
20. METHOD
Identification of flawed control measures and there causes
looking at component interactions.
Can identify constraints at each level
Can see dysfunctional interactions
Chain of events
21. COMPARISON OF
TECHNIQUES
Method Accident Focus on Levels of Primary Analytical Training
sequence safety analysis secondary approach need
barriers
CREAM No No 1-3 Primary Deductive & Expert
inductive
FRAM Yes Yes 1-2 Primary Deductive & Expert
inductive
Acci-Map No Yes 1-6 Primary Deductive & Expert
inductive
STAMP No Yes 1-6 Primary Deductive & Expert
inductive
22. REFERENCES
Hollnagel, E. (1998). Cognitive Reliability and Error Analysis Method. Oxford: Elsevier Science Ltd.
Hollnagel, E. (2012). FRAM – The Functional Resonance Analysis Method. Farnham: Ashgate.
Hollnagel, E. (2005). Functional Resonance Accident Model Method and examples. COGNITIVE SYSTEMS
ENGINEERING LABORATORY . University of Linköping.
Hollnagel, E. (2002). Understanding accidents-from root causes to performance variability. Human Factors and
Power Plants, 2002. Proceedings of the 2002 IEEE 7th Conference on , (pp. 1 - 1-6 ).
Kim, M., Seong, P., & Hollnagel, E. (2006). A probabilistic approach for determining the control mode in CREAM.
Reliability Engineering and System Safety , 191-199.
Leveson, N. G. (2004). A new accident model for engineering safer systems. Safety Science , 237-270.
Qureshi, Z. H. (2007). A review of accident modelling approaches for complex socio-technical systems. SCS '07
Proceedings of the twelfth Australian workshop on Safety critical systems and software and safety-related
programmable systems (pp. 47-59). Darlinghurst: Australian Computer Society.
Rasmussen, J. (1997). Risk management in a dynamic society: a modelling problem. Safety Sci. , 183–213.
Sklet, S. (2004). Comparison of some selected methods for accident investigation. Journal of hazardous
materials , 29-37.
Svedung, I., & Rasmussen , J. (2002). Graphic representation of accident scenarios: mapping system structure
and the causation of accident. Safety Science , 397-417.