Marine engineering systems failure analysis using extended failure modes and effects analysis with quality function deployment: maritime house of reliability

Purpose – This study develops the Maritime House of Reliability (M-HoR), an integrated model combining Quality Function Deployment (QFD) and Failure Modes and Effects Analysis (FMEA), to improve the reliability assessment of marine engineering systems by systematically embedding user requirements and accounting for failure interdependencies. Design/methodology/approach – The M-HoR framework translates marine engineers' reliability expectations into technical requirements by integrating QFD and FMEA. Severity is divided into weighted sub-criteria using the Analytic Hierarchy Process, and domino effects among failure modes are modelled. The methodology is demonstrated through a case study on crankcase explosion failures. Findings – The results show that considering domino effects and detailed severity parameters significantly alters failure prioritization compared to conventional FMEA. Specifically, Risk Priority Numbers changed by up to 299% and certain critical failure modes, previously underestimated, were reassigned as high risk, demonstrating improved precision and operational relevance of the proposed M-HoR approach. Research limitations/implications – The study is validated through a single case application. Future studies should explore broader system applications to confirm generalizability. Practical implications – The M-HoR framework provides a decision-support tool for marine engineers, enabling proactive risk management and contributing to safer and more sustainable ship-board operations. Social implications – Improving system reliability supports environmental protection and advances the shipping industry's decarbonization and safety goals. Originality/value – This research introduces a structured, user-centred reliability assessment framework for marine engineering systems. By integrating cascading failure analysis and refined severity evaluation, the M-HoR model addresses limitations in traditional methods and supports more resilient system design and maintenance practices.