Evaluating and Prioritising Delay Factors in Naval Ship Maintenance Using the Analytic Hierarchy Process: A Sri Lanka Navy Shipyard Case Study Dataset

This dataset supports the research article examining the causes of scheduled docking delays in naval ship and craft maintenance using the Analytic Hierarchy Process (AHP). The study focuses on identifying, classifying, and prioritising the most significant factors contributing to maintenance schedule overruns in a naval shipyard context.The dataset comprises expert judgment data collected through a structured questionnaire based on pairwise comparisons. Experienced naval engineers and maintenance professionals evaluated the relative importance of delay causes using Saaty’s fundamental scale. The delay factors were identified through an extensive literature review and expert panel consultation and were classified into six major categories: Material, Machine, Man, Method, Measurement, and Environment.The dataset includes:Pairwise comparison matrices for Level 1 (main delay categories) and Level 2 (individual delay causes)Normalised matrices and derived priority vectorsConsistency Index (CI) and Consistency Ratio (CR) calculations to validate judgment reliabilityFinal relative weights and rankings of delay factors at both category and overall levelsDue to organisational confidentiality constraints, raw operational and financial data are not included. However, the provided dataset fully captures the analytical structure and numerical inputs required to replicate the AHP methodology using comparable expert data.This dataset is intended for use by researchers, practitioners, and policymakers interested in ship maintenance management, naval logistics, project delay analysis, and multi-criteria decision-making methods. It can support comparative studies across shipyards, validation of delay prioritisation frameworks, and further methodological research in maritime operations and offshore asset maintenance.