As global energy production progressively turns toward a green environment and economy, one of the safety challenges to the maritime industry that has arisen lies within offshore wind farms (OWFs). As renewable sources of energy whose numbers are rapidly expanding, their impact to the safety of navigation of the ships that navigate in their vicinity ought to be examined further. An ever-growing number of OWFs has led to safety concerns that have never been taken into consideration before. This article gives a structured quantitative analysis and an in-depth review of the literature connected to the safety of navigation, collision probability, and risk assessment that OWFs pose to all maritime industry agents. In this article, the main concerns of the impact of OWFs to the safety of navigation are analyzed using a combination of both the PRISMA and PICOC methodologies. Various types of scientific papers such as journal articles, conference proceedings, MSc theses, PhD theses, and online works of research are collated into a detailed bibliometric analysis and categorized by the most relevant parameters providing valuable perspectives on the current state of art in the field. The findings of this research emphasize the need for a further and more thorough analysis on the theoretical installment of OWFs and their inevitable impact on increasing maritime traffic complexity. The results of this article can form a strong basis for further scientific development in the field and can give useful insights to all maritime industry stakeholders dealing with OWFs.

Dynamic positioning (DP) operations are safety-critical maritime activities in which technical system performance, environmental conditions and human decision-making interact continuously. Previous research presented a prediction model based on binary logistic regression that estimates the likelihood of human-error-related DP incidents, identifying the percentage of thrusters online as the significant predictor, using IMCA-reported data from 2007–2015. This study evaluates whether the previously developed prediction model remains valid when applied to a more recent IMCA dataset, with DP incidents from 2016 to 2025. A retrospective documentary analysis was conducted, and 77 incidents met the inclusion criteria for statistical analysis. Human-related factors were identified as a main or secondary cause in 35 cases, representing 45.5% of the analysed sample. The original thruster-based relationship was not reproduced in the updated drilling subset, where the percentage of thrusters online did not distinguish between human-related and non-human-related incidents. Applying the previous model resulted in poor discriminatory performance (AUC = 0.541), indicating that the original relationship between thruster availability and human-related incidents was no longer observed. Additional regression analyses found no statistically significant association between the selected operational, technical or environmental variables and human-related causation. These findings suggest that historical prediction models should be re-evaluated before being applied to contemporary DP operations. They also indicate that the variables available in IMCA reports alone are insufficient to explain human-related incident causation, highlighting the need for future studies to investigate additional human and organisational factors.