Risk assessment in maritime domain is one of the most cited topics since maritime transportation poses potential hazard for human life, marine environment and property. To mitigate risk and enhance safety awareness in maritime transportation, safety researchers have been seeking proactive solutions. This article prompts a quantitative risk-based approach combining interval type-2 fuzzy sets (IT2FSs) with failure mode and effect analysis (FMEA) to perform a comprehensive risk analysis. Thus, potential failure modes and their effects are revealed by calculating risk prioritisation numbers (RPNs). Whilst the FMEA method provides a robust risk analysing tool with relevant control options, the IT2FSs deals with ambiguity and vagueness of linguistic assessment of decision-makers through the FMEA. Hence, expert’s linguistic assessment in risk assessment can be transformed into useful information in terms of enhancing safety and pollution prevention in maritime industry. To demonstrate the proposed approach, potential failures and effects of a real shipboard oil spill case are handled. The findings show that incomplete information exchanged with local maritime authorities, malfunction of oil skimmer and poor organization of shoreline clean-up team are the most important failures during case of oil spill. The proposed approach provides not only theoretical insight into the maritime transportation industry but also practical contributions to chemical/oil tanker safety and environmental protection by mitigating risk in terms of technical or operational aspects.

Oil/chemical tanker ships carry a large volume of liquefied chemical cargoes in bulk condition. Chemical cargoes can be hazardous and most of them being flammable and/or toxic. It may pose acute dangers for human life and maritime environment. Risk assessment is of paramount importance to enhance operational safety and to protect environment for oil/chemical tanker ships. This paper aims at conducting an extensive risk analysis for oil/chemical tanker pollution due to leakage since the consequences can be fatal for human and marine environment. To accomplish this, fault tree analysis (FTA) is used. The failure occurrence probabilities of basic event (BE) of FT are calculated under fuzzy logic. The extended CREAM (Cognitive reliability and error analysis method) approach is used to determine human-oriented errors in FT since human error contributes the most to various types of maritime accidents. The outcomes of the paper can be helpful to minimize chemical leakage pollution risks and to improve operational safety in cargo loading/discharging process in oil/chemical tankers.

The role of human factor plays a critical role in the safe and clean operation of maritime industry. Human error prediction can be beneficial to assess risk in maritime industry since shipping activities can pose potential hazards to human life and maritime ecology. The aim of this paper is to propose a risk assessment tool by considering the role of human factor. Hence, the desired safety control level in maritime transportation activities can be ascertained. In the proposed approach, a Success Likelihood Index Method (SLIM) extended with fuzzy logic is used to calculate human error probability (HEP). Severity of consequences are adopted in the proposed approach to assess risk. The quantitative risk assessment approach under fuzzy SLIM methodology will be applied to a very specific case on-board ship: Ballast Water Treatment (BWT) system. In order to improve consistency of research and minimize subjectivity of experts' judgments, the paper adopts the dominance factor which is used to adjust the impact level of experts' judgments in the aggregation stage of the methodology. The paper aims at not only highlighting the importance of human factor in maritime risk assessment but also enhancing safety control level and minimizing potential environmental impacts to marine ecology.

The current industrial environment relies heavily on maritime transportation. Despite the continuous technological advances for the development of innovative safety software and hardware systems, there is a consistent gap in the scientific literature regarding the objective evaluation of the performance of maritime operators. The human factor is profoundly affected by changes in human performance or psychological state. The difficulty lies in the fact that the technology, tools, and protocols for investigating human performance are not fully mature or suitable for experimental investigation. The present research aims to integrate these two concepts by (i) objectively characterizing the psychological state of mariners, i.e., mental workload, stress, and attention, through their electroencephalographic (EEG) signal analysis, and (ii) validating an innovative safety framework countermeasure, defined as Human Risk-Informed Design (HURID), through the aforementioned neurophysiological approach. The proposed study involved 26 mariners within a high-fidelity bridge simulator while encountering collision risk in congested waters with and without the HURID. Subjective, behavioral, and neurophysiological data, i.e., EEG, were collected throughout the experimental activities. The results showed that the participants experienced a statistically significant higher mental workload and stress while performing the maritime activities without the HURID, while their attention level was statistically lower compared to the condition in which they performed the experiments with the HURID (all p < 0.05). Therefore, the presented study confirmed the effectiveness of the HURID during maritime operations in critical scenarios and led the way to extend the neurophysiological evaluation of the HFs of maritime operators during the performance of critical and/or standard shipboard tasks.