The maintenance of critical maritime infrastructure is essential for ensuring the safe, reliable, and efficient operations of marine seaports. This paper proposes a novel fuzzy multi-criteria decision framework for evaluating the maintenance practices and culture of maintenance-critical maritime infrastructure, such as port loading and unloading machinery and equipment. The proposed framework incorporates three distinct multi-criteria decision-making tools Step-wise Weight Assessment Ratio Analysis, Weighted Aggregate Sum Product Assessment, and Technique for Order of Preference by Similarity to Ideal Solution. Fuzzy logic is incorporated into the framework to enhance the precision and robustness of the evaluation process. To form the basis of the assessment, the framework is structured around five key maintenance practice criteria: planning and scheduling; data collection and analysis; documentation and record keeping; maintenance personnel training; and competency, and four important maintenance culture criteria: leadership commitment, proactive and preventive approach, safety and compliance focus, and continuous improvement and learning. To validate the framework, an empirical evaluation was conducted, analyzing maintenance practices and culture across six Nigerian seaports. Data collection uses a questionnaire administered to relevant maintenance experts in the ports, ensuring a comprehensive and expert-informed analysis. The data collected was then analyzed using the fuzzy multi-criteria decision framework. The results provide valuable and actionable insights into the current maintenance practices and maintenance culture of the ports, identifying areas for improvement.

Boat collisions pose severe threats to maritime safety, economic activity, and environmental sustainability. Conventional risk assessment methods—such as Failure Mode and Effects Analysis, and Fault Tree Analysis—are widely applied but remain inadequate for addressing the uncertainty, subjectivity, and interdependency of risk factors in complex maritime environments. This study proposes a fuzzy Multi-Criteria Decision-Making framework for the risk assessment of boat collisions. The model integrates fuzzy logic with Analytic Hierarchy Process for criterion weighting and the Technique for Order Preference by Similarity to the Ideal Solution for risk ranking. Fuzzy logic is employed to capture linguistic expert judgments and to manage vague or incomplete data, which are common challenges in marine operations. Key collision risk factors—human error, boat engine system failure, environmental conditions, and intentional threats—are identified through literature review, incident data analysis, and expert consultation. A comparative analysis with a baseline non-fuzzy model demonstrates the added value of the fuzzy-integrated framework, showing improved capacity to handle imprecision and uncertainty. The model outputs not only prioritise risk rankings but also support the identification of critical control actions and effective safety measures. A case study of Nigerian waters illustrates the practicality of the framework in guiding risk mitigation strategies and informing policy decisions under uncertainty.