1. OVERVIEW OF
SYSTEMIC
MODELING
APPROACHES
ROSS APTED

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

15. HIERARCHICAL MODEL
OF SOCIO-TECHNICAL
SYSTEMS
(Rasmussen, 1997)

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.

19. STAMP
Hierarchical
Command &
Control
Structure of the
Black Hawk
fratricide
(Qureshi, 2007)

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.