Overview of Systemic Modeling Approaches


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Overview of Systemic Modeling Approaches

  2. 2. TASKTo 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. 3. SYSTEMIC APPROACHConsiders the performance of the system as a whole. Organization Environmental Human TechnicalSystem is view as many components interacting causing aequilibrium.Systemic can evolve dynamicallyFlawed interactions between components could causesystem to be thrown out of balance Accident
  4. 4. METHODS REVIEWEDCognitive 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. 5. CREAM - COGNITIVERELIABILITY AND ERRORANALYSIS METHOD(Hollnagel E. , Cognitive Reliability and Error Analysis Method., 1998)Background:Developed by Erik Hollnagel in 1998Cognitive 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 accidentanalysis or performance predictions
  6. 6. COGNITIVE SYSTEMENGINEERINGTechnology has changed the way in which humans work Manual tasks Knowledge heavy(thinking) tasks.Change has lead to new problems in human performancecausing 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. 7. SOLUTION - CREAMAIM:1. To identify components of the systems which relies on human cognition2. 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. 8. METHODControl 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-0Reliability interval – The probability of action failures
  9. 9. METHODCommon PerformanceConditions:The minimum number of factorsthat are vital in order to describethe context of the system.State of each CPC is assessed byanalyst (Kim, Seong, & Hollnagel, 2006)
  10. 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. 11. FRAM - FUNCTIONALRESONANCE ANALYSISMETHOD(Hollnagel E. , FRAM – The Functional Resonance Analysis Method, 2012)Background:Developed by Erik Hollnagel in 2004Performance variability Performance in a system whither internal, externaldynamically fluctuates. Variability in complex systems isnormal.Key idea:Models how components of a system resonate and interactwith each other causing the system to lose balance leadingto accidents.
  12. 12. METHOD1. Identify Vital system functions and categories functions (Hollnagel E. , Functional Resonance Accident Model Method and examples, 2005)
  13. 13. METHOD 2. Describe potential variability of system.3. Identifyfunctions that havedependency thatmay effect thesystem4. Identify barriersfor variability andspecify requiredperformancemonitoring (Hollnagel E. , Functional Resonance Accident Model Method and examples, 2005)
  14. 14. ACCI-MAP(Rasmussen, 1997)Background:Developed by J. Rasmussen and I. Svedung in 2000Utilizes Rasmussen hierarchical model of socio-technicalsystemsKey idea:A model that describes an accident in terms of differentlevels of socio-technical systems
  16. 16. METHODCause-Consequence chart that extends across thehierarchical levels. (Transportation of dangerous goods) (Svedung & Rasmussen , 2002)
  17. 17. STAMP - SYSTEMS-THEORETICACCIDENT MODEL ANDPROCESSES(Leveson, 2004)Background:Developed by Nancy Leveson in 2004System theory Systems are self regulating, this is achieved through feedback loopsKey idea:Accidents do not occur as a result of individual componentfailures. Accidents are a results of external forces anddysfunctional interactions of components not being correctlymanaged .
  18. 18. METHOD1. Development of hierarchical control structure which show the interactions between different system components, safety regulations and constraints.
  19. 19. STAMPHierarchicalCommand &ControlStructure of theBlack Hawkfratricide(Qureshi, 2007)
  20. 20. METHODIdentification of flawed control measures and there causeslooking at component interactions. Can identify constraints at each level Can see dysfunctional interactions Chain of events
  21. 21. COMPARISON OF TECHNIQUESMethod Accident Focus on Levels of Primary Analytical Training sequence safety analysis secondary approach need barriersCREAM No No 1-3 Primary Deductive & Expert inductiveFRAM Yes Yes 1-2 Primary Deductive & Expert inductiveAcci-Map No Yes 1-6 Primary Deductive & Expert inductiveSTAMP No Yes 1-6 Primary Deductive & Expert inductive
  22. 22. REFERENCESHollnagel, 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 SYSTEMSENGINEERING LABORATORY . University of Linköping.Hollnagel, E. (2002). Understanding accidents-from root causes to performance variability. Human Factors andPower 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 07Proceedings of the twelfth Australian workshop on Safety critical systems and software and safety-relatedprogrammable 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 hazardousmaterials , 29-37.Svedung, I., & Rasmussen , J. (2002). Graphic representation of accident scenarios: mapping system structureand the causation of accident. Safety Science , 397-417.