1. Usability of accident and incident reports for evidence-based risk modeling – A case study on ship grounding reports
- Author
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Jari Nisula, Arsham Mazaheri, Jakub Montewka, Pentti Kujala, School of Engineering [Aalto], Aalto University, Interactive Critical Systems (IRIT-ICS), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Minimizing risks of maritime oil transport by holistic safety strategies (MIMIC) project, Winter Navigation Risks and Oil Contingency Plan (WinOil) project., European Regional Development Fund, The Central Baltic INTERREG IV A Programme 2007–2013, South-East Finland – Russia ENPI CBC 2007–2013, the City of Kotka, Kotka–Hamina Regional Development Company (Cursor Oy), Centre for Economic Development, and Transport and the Environment of Southwest Finland (VARELY)., Department of Applied Mechanics, and Aalto-yliopisto
- Subjects
Engineering ,Evidence-based practice ,government.form_of_government ,Poison control ,Near miss ,Computer security ,computer.software_genre ,Occupational safety and health ,HFACS ,Ship grounding ,[INFO]Computer Science [cs] ,Accident and incident reports ,Near-miss ,Safety Factor ,Evidence-based risk modeling ,Safety, Risk, Reliability and Quality ,ta214 ,business.industry ,Public Health, Environmental and Occupational Health ,Human factors and ergonomics ,Usability ,Risk analysis (engineering) ,government ,Human Factors Analysis and Classification System ,business ,Safety Research ,computer ,Incident report - Abstract
International audience; This paper presents study of 115 grounding accident reports from the Safety Investigation Authority of Finland and Marine Accident Investigation Branch of the UK, as well as 163 near-miss grounding reports from ForeSea and Finnpilot incident databases. The objective was to find the type of knowledge that can be extracted from such sources and discuss the usability of accident and incident reports for evidence-based risk modeling. A new version of Human Factors Analysis and Classification System (HFACS) is introduced as a framework to review the accident reports. The new positive taxonomy as Safety Factors, which are based on high level positive functions that are prerequisite for safe transport operations, is used for reviewing the incident reports. Accident reports are shown as a reliable source of evidence to extract the most significant contributing factors in the events. Mandatory incident reports are considered useful for understanding the effective barriers as risk control measures. Voluntary incident reports, though, are seen as not very reliable in their current form to be used for evidence-based risk modeling.
- Published
- 2015
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