Advertisement

Use of Bayesian Network for Human Reliability Modelling: Possible Benefits and an Example of Application

  • Maria Chiara LevaEmail author
  • Peter Friis Hansen
Chapter
  • 851 Downloads
Part of the Springer Series in Reliability Engineering book series (RELIABILITY)

Abstract

The scope of the present work is to report an action research project applied to the relationship of task and cognitive workload support on one of the most important aspects of an airport: ground handling. At the beginning of the project workload management was not in the scope of work but as the project progressed and preliminary results and feedback were gained the researcher came to realize that some form of workload management support was also achieved as a by-product. The present chapter is an attempt to account for what was achieved and how. Safe and efficient ground handling during departure and arrival of an aircraft requires coordinated responsibilities amongst qualified operators collaborating together simultaneously in a time constrained environment. The context is one of medium-high workload due to the number of activities covered in a short time, such as: passenger, baggage and cargo handling, aircraft loading, the provision and use of ground support equipment, etc. This chapter presents the introduction of a tool aimed at performance monitoring and task support and discusses how the use of it can play a key role in the adequate management of workload by operators in Ground Handling. The core elements of the tool under analysis are electronic checklist and digitized shift handover, and it aims at highlighting how they have impacted performance, reducing operational and human related issues.

Keywords

Cognitive Reliability And Error Analysis Method (CREAM) Collision Route Human Error Probability (HEP) Contextual Control Model Bridge Layout 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Colreg (1972) Convention on the international regulations for preventing collisions at seaGoogle Scholar
  2. Cowell RG, Dawid AP, Lauritzen SL, Spiegelhalter DJ (1999) Probabilistic networks and expert systems. Springer, New YorkzbMATHGoogle Scholar
  3. Friis-Hansen A (2000) Bayesian networks as a decision support tool in marine applications. PhD thesis. Department of Naval Architecture and Offshore Engineering, Technical University of Denmark, DecemberGoogle Scholar
  4. Friis-Hansen P, Terndrup Pedersen P (1999) Risk analysis of conventional and solo watch keeping. Department of Naval Architecture and Offshore Engineering, 65 p. www.mek.dtu.dk
  5. Galvagni R, Clementel S (1989) Risk analysis as an instrument of design. In: Cumo M, Naviglio A (eds) Safety design criteria for industrial plant. CRC Press, Boca RatonGoogle Scholar
  6. Groth K, Wang C, Mosleh A (2010) Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems. Reliab Eng Syst Saf 95:1276–1285CrossRefGoogle Scholar
  7. Hollnagel E, Cacciabue C (1991) Modeling cognition and erroneous actions in system simulation contexts. Paper presented at 3rd European meeting on ‘Cognitive science approaches to process control,’ Cardiff, 2nd–6th SeptemberGoogle Scholar
  8. Hollnagel E (1993) Human reliability analysis: context and control. Academic, LondonGoogle Scholar
  9. Hollnagel E (1998) Cognitive reliability and error analysis method CREAM. Elsevier, OxfordGoogle Scholar
  10. Laplace PS (1819) A philosophical essay on probabilities. WileyGoogle Scholar
  11. Leva MC, Hansen PF, Sonne Ravn E, Lepsøe A (2006) SAFEDOR: a practical approach to model the action of an officer of the watch in collision scenarios. In: Proceedings of ESREL Conference, Estoril Portugal, Taylor & Francis GroupGoogle Scholar
  12. Lützen M, Friis-Hansen P (2003) Risk reducing effect of AIS implementation on collision risk. In: Proceedings of world maritime technology conference, 17–20 Oct 2003, San FranciscoGoogle Scholar
  13. Neisser U (1976) Cognition and reality: principles and implications of cognitive psychology. Freeman, New YorkGoogle Scholar
  14. Ritter F, Shadbolt N, Elliman D, Young R, Gobet F, Baxter G (2003) Techniques for modeling human performance in synthetic environments: a supplementary review. Human Systems Information Analysis Center, Wright-Patterson Air Force Base, Dayton, OHCrossRefGoogle Scholar
  15. Swain AD, Guttmann HE (1983) Handbook on human reliability analysis with emphasis on nuclear power plant application. NUREG/CR-1278, SAND 08-0200 R X, ANGoogle Scholar
  16. Trucco P, Cagno E, Ruggeri F, Grande O (2008) A Bayesian belief network modelling of organisational factors in risk analysis: a case study in maritime transportation. Reliab Eng Syst Saf 93(6):845–856CrossRefGoogle Scholar
  17. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Dublin Institute of Technology School of Environmental ScienceDublinIreland
  2. 2.Det Norske VeritasOsloNorway

Personalised recommendations