The COSYCO Concept: an Indicator for COmparing SYstem COnfigurations | Amsterdam University Press Journals Online
2004
Volume 1, Issue 1
  • ISSN: 2589-6725
  • E-ISSN: 2589-6733

Abstract

Abstract

The recently introduced Risk SituatiOn Awareness Provision (RiskSOAP) methodology suggested an indicator to measure the distance between the configuration of a real system and its ideal version or between various system versions. It considers the (in)existence or (mal)functioning of system components, processes and connections based on a binary approach. However, in practice safety requirements can be fulfilled to some degree and each system component might have a different impact on system outcomes. This work suggests the Comparing System Configurations (COSYCO) indicator which introduces (1) the use of continuous values for the behaviour of system components, (2) the inclusion of weights according to the hierarchal system level to which each component belongs, and (3) the consideration of the outgoing connections of each component with other system components. Both RiskSOAP and COSYCO are based on the STPA hazard analysis which is a systematic technique used to define the components and the requirements that the system should ideally meet to achieve its objectives. To demonstrate the applicability and sensitivity of COSYCO, we applied it to a published case for small drones. Drones with same overall differences in the satisfaction of requirements concluded to different values when applying COSYCO, indicating the increased sensitivity of the specific indicator when compared to the RiskSOAP. We envisage that the metric proposed in this work is a first practical and realistic approach to the quantification of the distance between the optimal design and current system states as well amongst various systems and their versions over time.

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References

  1. Alzeban, A. and Gwilliam, D., 2014. Factors affecting the internal audit effectiveness: A survey of the Saudi public sector. Journal of International Accounting, Auditing and Taxation, 23(2), 74–86.
    [Google Scholar]
  2. Antonsen, S., Almklov, P., & Fenstad, J. (2008). Reducing the gap between procedures and practice–lessons from a successful safety intervention. Safety science monitor, 12(1), 1–16.
    [Google Scholar]
  3. Arenius, M., & Sträter, O. (2013). Resilience engineering in railways—results from a systemic accident and event analysis in German railways in Steenbergen, R. D. J. M., van Gelder, P. H. A. J. M., Miraglia, D. & Vrouwenvelder, A. C. W. M. (Eds), Safety, Reliability and Risk Analysis: Beyond the Horizon, 423–428.
    [Google Scholar]
  4. Blandford, A., Furniss, D., & Vincent, C. (2014). Patient safety and interactive medical devices: realigning work as imagined and work as done. Clinical risk, 20(5), 107-110.
    [Google Scholar]
  5. Borys, D. (2012). The role of safe work method statements in the Australian construction industry. Safety science, 50(2), 210–220.
    [Google Scholar]
  6. Boschma, R. (2005). Proximity and innovation: a critical assessment. Regional studies, 39(1), 61–74.
    [Google Scholar]
  7. Bourrier, M. (1996). Organizing maintenance work at two American nuclear power plants. Journal of contingencies and crisis management, 4(2), 104–112.
    [Google Scholar]
  8. Chatzimichailidou, M. M., & Dokas, I. M. (2016a). Introducing RiskSOAP to communicate the distributed situation awareness of a system about safety issues: an application to a robotic system. Ergonomics, 59(3), 409–422.
    [Google Scholar]
  9. Chatzimichailidou, M. M., & Dokas, I. M. (2016b). RiskSOAP: introducing and applying a methodology of risk self-awareness in road tunnel safety. Accident Analysis & Prevention, 90, 118–127.
    [Google Scholar]
  10. Chatzimichailidou, M. M., Karanikas, N., & Plioutsias, A. (2017). Application of STPA on Small Drone Operations: A Benchmarking Approach. Procedia Engineering, 179, 13–22.
    [Google Scholar]
  11. Chatzimihailidou, M. M., Karanikas, N. & Dokas, I. (2016). Measuring Safety Through the Distance Between System States with the RiskSOAP Indicator. Proceedings of the 1st International Cross-industry Safety Conference, Amsterdam, 3-4 November 2016, Journal of Safety Studies, 2(2), 5–17. doi:10.5296/jss.v2i2.10436.
    [Google Scholar]
  12. Chatzimichailidou, M. M., Stanton, N. A., & Dokas, I. M. (2015). The concept of risk situation awareness provision: towards a new approach for assessing the DSA about the threats and vulnerabilities of complex socio-technical systems. Safety science, 79, 126–138.
    [Google Scholar]
  13. Clay-Williams, R., Hounsgaard, J., & Hollnagel, E. (2015). Where the rubber meets the road: using FRAM to align work-as-imagined with work-as-done when implementing clinical guidelines. Implementation Science, 10(1), 125.
    [Google Scholar]
  14. Dekker, A.H. and Colbert, B.D., 2004, January. Network robustness and graph topology. In Proceedings of the 27th Australasian conference on Computer science-Volume 26 (pp. 359–368). Australian Computer Society, Inc.
    [Google Scholar]
  15. Dekker, S. W., Suparamaniam, N., & Veritas, D. D. N. (2005). Divergent images of decision making in international disaster relief work. Ljungbyhed, Sweden: Lund University School of Aviation.
    [Google Scholar]
  16. Horwitz, B. (2003). The elusive concept of brain connectivity. Neuroimage, 19(2), 466–470.
    [Google Scholar]
  17. Festinger, L., Schachter, S., & Bach, K. (1950). "Social pressures in informal groups". New York: Harper.
    [Google Scholar]
  18. Jones, Kevin K., (2013). "The Impact of Legislation on the Organization: Evaluating the Impact of Corporate Governance Regulation on the Internal Audit Function". (Dissertation) USA: Georgia State University. Retrieved 5 October 2017 from http://scholarworks.gsu.edu/bus_admin_diss/22.
    [Google Scholar]
  19. Leveson, N. (2011). Engineering a safer world: Systems thinking applied to safety. USA: MIT Press.
    [Google Scholar]
  20. Lundberg, H. (2008). Geographical proximity effects and regional strategic networks (Doctoral dissertation). Uppsala Universiteit. Retrieved 10 Septmber 2017 from http://www.diva-portal.org/smash/get/diva2:171790/FULLTEXT01.pdf.
    [Google Scholar]
  21. Mason, K., & Chakrabarti, R. (2017). The role of proximity in business model design: Making business models work for those at the bottom of the pyramid. Industrial Marketing Management, 61, 67–80.
    [Google Scholar]
  22. Newcomb, T.M. (1960). Varieties of interpersonal attraction. In D.Cartwright & A.Zander (Eds.), "Group dynamics: Research and theory" (2nd ed., pp. 104–119).
    [Google Scholar]
  23. Plioutsias, A., Karanikas, N., & Chatzimihailidou, M. M. (2017). Hazard Analysis and Safety Requirements for Small Drone Operations: To What Extent Do Popular Drones Embed Safety?. Risk Analysis, doi:10.1111/risa.12867.
    [Google Scholar]
  24. Stanton, N. A. (2014). Representing distributed cognition in complex systems: how a submarine returns to periscope depth. Ergonomics, 57(3), 403–418.
    [Google Scholar]
  25. Woltjer, R., Pinska-Chauvin, E., Laursen, T., & Josefsson, B. (2015). Towards understanding work-as-done in air traffic management safety assessment and design. Reliability Engineering & System Safety, 141, 115–130.
    [Google Scholar]
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  • Article Type: Research Article
Keyword(s): COSYCO; RiskSOAP; STPA; System Configuration; System Controllability; System Responsibility
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