Understanding and managing safety challenges in small fishing boats in remote communities

Domeh, Daniel Vindex Kwabla (2023) Understanding and managing safety challenges in small fishing boats in remote communities. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Abstract

This thesis studied the development of probabilistic safety assessment (PSA) tools and methodologies for small fishing boats (SFB) use. The tools and methodologies developed were applied to case study scenarios, and they showed high prospects in identifying safety challenges when SFBs are fishing. Because, in most cases, SFBs in remote fishing communities lack adequate safety equipment to prevent accidents at sea, the PSA tools and methodologies are primarily aimed at these communities. The SFB size in the marine environment, amidst harsh sea conditions, endangers fishers’ safety during fishing voyages. Lapses that may be present in the SFB safety regulation and monitoring at individual country levels allow some SFBs not to have onboard the appropriate equipment to understand, monitor, and manage the safety challenges encountered. These safety challenges are rooted in the accidents SFBs encounter. Although man or person overboard, main propulsion system failure, loss of situational awareness, and loss of stability were frequent in most SFB accident and incident databases, the research on these mostly led to only uncovering their causation factors. Linking these factors and their incidents to yield PSA tools capable of explaining how the incidents occur was yet to be done. The quantitative risk analysis (QRA) and Bayesian network (BN) modelling were identified through a literature review as rigorous methods for developing PSA tools and methodologies, so they were applied accordingly to the named accidents and incidents. The novel contributions the thesis made to the body of knowledge in SFB safety and maritime research, in general, are (1) the development of a unique methodology called the goal-directed risk identification technique (Goal-DRIT) for listing risk factors in highly complex systems; (2) naïve Bayes’ application to fill conditional probability tables (CPT) with probability scores; (3) development of a rule-based system for guiding subject-matter experts in probability elicitation exercises, to minimise variability in experts scores and (4) development of independence of causal influence model using De Morgan gates for both qualitative risk analysis and probabilistic risk analysis. The thesis study is recommended for the fishing industry (particularly the SFB sector), national and international maritime administrations, and SFB safety researchers.

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