Given the inherent uncertainties and data scarcity in fishing operations, how can risk be effectively assessed? This paper proposes a method using fuzzy set theory (FST) to model the occurrence likelihood and consequences of failure for hazards identified on fishing vessels. The author addresses the use of conventional probabilistic risk assessment and its unsuitability due to the high degree of uncertainty involved with the data. This method uses fault tree analysis to calculate the fuzzy probability of system failure, along with four different consequence categories. Risk in linguistic terms of basic events is determined by combining occurrence likelihood and consequences.The method is demonstrated using a hydraulic winch operating system of a fishing vessel. This application of fuzzy set theory offers a valuable tool for improving safety and reliability in the fishing industry. The method is further defuzzified to produce a risk ranking, increasing comprehension for the operator.
This study is highly relevant to the _International Journal of Reliability, Quality and Safety Engineering_. By applying fuzzy set theory to improve risk assessment in fishing vessels, the paper aligns with the journal's goal of promoting safety and reliability in engineering systems.