Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

A text-based approach for identification of RIFs in Arctic shipping
Shan-shan Fu1, Yue Zhang1, Zi-zheng Hu1, Yong-tao Xi2, Bing Han3, Shen-ping Hu2
1College of Transport & Communications, Shanghai Maritime University
2College of Merchant Marine, Shanghai Maritime University
3Shanghai Ship and Shipping Research InstituteShanghai, China
factors causing the collision. Fu et al. (2016; 2018) proposed a multifactor coupling model based on the ship stuck in ice. Kum et al. (2015)
sorted out the root causes of ship accidents in Arctic waters andestablished a fault tree model for ship collision and grounding accidents.

ABSTRACTThe opening of the Arctic sea routes attracts global attention. Identifying
the risk influencing factors (RIFs) is critical for proposing target risk
control options (RCOs) in Arctic shipping. This paper presents a textbased approach to identify critical RIFs using multi-source data,including maritime accident investigation reports and literature. A
mapping model is proposed for interpreting the relationship between theidentified critical RIFs and the associated accident scenarios, such as
collision, grounding, and ship-ice/iceberg collision. The results showthat wind, visibility, drift ice, ridge ice/iceberg, ship speed, andcommunication equipment failure are mutual factors that induce various
maritime accidents in Arctic shipping.

The above studies have conducted a relatively comprehensive
identification of RIFs in Arctic shipping under a single accident scenario.
However, there is a lack of research on the complex coupling relationshipbetween multiple accident scenarios and the RIFs. Because of this, thispaper proposes a text-based approach to identify the critical RIFs thatinduce maritime accidents in Arctic waters and obtain the relationshipbetween these factors and accident scenarios (e.g., collision, grounding,ship stuck in ice, ship-ice/iceberg), based on maritime accident
investigation reports (MAIRs) and the related literature.

KEY WORDS: Marine safety; Arctic shipping; risk influencing factor;
The rest of this paper is organized as follows. Section 2 introduces thetext-based approach for identifying the RIFs in Arctic shipping. Section
3 gives a brief overview of the data source. Section 4 presents anapplication of the proposed method through a case study that uses
MAIRs and literature mentioned in Section 2 and discusses therelationship between RIFs and accident scenarios in Arctic shipping.
Finally, section 5 summarizes this study and proposes relevant
conclusions.

maritime accident investigation report; text mining

INTRODUCTION
In recent years, with global warming and the diminishing extent of Arctic
sea ice, the conditions for transportation activities of Arctic shipping
have been greatly improved and the volume of ship traffic has increased
rapidly. This has increased the happening of maritime accidents in Arctic
shipping. According to the Safety and Shipping Review issued by AGCS
in 2021, there were 520 ship navigation accidents that occurred in Arctic
waters from 2011 to 2020. Maritime accidents may severely restrict thedevelopment of the Arctic sea routes. Therefore, it is significant for risk
analysis of ship operations in ice-cover waters and proposing associatedrisk control options (RCOs) for reducing maritime accidents in Arcticshipping.

METHOD
A test-based approach is used to identify the RIFs that induce maritime
accidents and express the mapping relationship between RIFs andmultiple maritime accidents in Arctic shipping, based on MAIRs in
Arctic waters and literature related to risk management of Arctic
shipping. The specific research steps are shown in Fig.1.

RIFs analysis is a critical issue for risk management in Arctic shipping.
Khan et al. (2018; 2020) and Obisesan et al. (2018) extracted the RIFs of
ship-ice collision accidents in the Arctic waters from three aspects ofenvironmental factors, ship-related factors and human factors. Aziz et al.
(2019) established a structured bow-tie model to assess the risk of fire/
explosion and machinery damage under the influences of ship failure andhuman error. Zhang et al. (2019) considered the impact of theenvironment on personnel and identified human factors in collision
accidents between assisted ships and icebreakers. Afenyo et al. (2017)
established a ship-iceberg collision accident model to derive the main

Step 1: Data collection. The data used for the identification of the RIFs
in Arctic shipping are acquired from the global MAIRs in Arctic waters
and related literature.
Step 2: Identification of RIFs. Based on the collected MAIRs andliterature in Step 1, the potential RIFs are identified by an in-depth
analysis of these text documents from environmental, ship-related,
human and organizational aspects. Then, the critical RIFs are selected bystatistical analysis of the frequency of the potential RIFs involved in theMAIRs and literature.

1310