Use of HFACS and fault tree model for collision risk factors analysis of icebreaker assistance in ice-covered waters

Mingyang Zhang, Di Zhang*, Floris Goerlandt, Xinping Yan, Pentti Kujala

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

97 Sitaatiot (Scopus)
36 Lataukset (Pure)

Abstrakti

With the global warming and a large amount of sea ice melting, the available Arctic Sea Route has greatly enhanced the value of Arctic shipping. Ship operations under icebreaker assistance have become an essential way to facilitate the safe navigation of merchant vessels sailing through the Arctic Sea Route in ice-covered waters, but they can also put the crew and the ship in danger caused by a possible collision between the assisted ship and the icebreaker. In this paper, a dedicated Human and Organizational Factors (HoFs) model of ship collision accidents between an assisted ship and an icebreaker is developed and analyzed with the aim to identify and classify collision risk factors. First, a modified model of the Human Factors Analysis and Classification System (HFACS) for collision accidents between a ship and an icebreaker in ice-covered waters is proposed, which helps to analyze ship collision reports. Then, a Fault Tree Analysis (FTA) model is utilized to analyze the fundamental collision risk factors according to the statistical analysis of accident reports and expert judgments based on the HFACS-SIBCI model. Finally, qualitative analysis is carried out to analyze collision risk factors under icebreaker assistance, where Risk Control Options (RCOs) are formulated. An important guidance for the risk control of ship collisions during icebreaker assistance in ice-covered waters is provided for lawmakers and shipping companies.

AlkuperäiskieliEnglanti
Sivut128-143
Sivumäärä16
JulkaisuSafety Science
Vuosikerta111
Varhainen verkossa julkaisun päivämäärä1 tammikuuta 2018
DOI - pysyväislinkit
TilaJulkaistu - 1 tammikuuta 2019
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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