A systematic literature review of RAM+ analysis: methodologies, applications, and gaps

Purpose This review underscores the importance of reliability, availability, maintainability (RAM) + analysis in assessing system performance and safety parameters while identifying risk-based improvements. The insights, gaps, and tendencies identified serve as foundation for future improved research studies and applications in this topic. Design/methodology/approach This study presents a systematic literature review (SLR) on RAM analysis methodologies and derivations (especially RAMI, RAMS, and RAMSS), their applications, and research gaps across several engineering domains. To address different methodological derivations, the term “RAM+” is proposed. The review follows a well-established SLR framework, covering planning, searching, data collection, analysis, synthesis, interpretation, reporting, and review updating activities. These activities resulted in the selection of 100 articles, based on predefined inclusion and exclusion criteria. Findings The analysis reveals a wide range of techniques applied in RAM + studies, including functional analysis, failure mode and effects analysis (FMEA)/failure mode, effects, and criticality analysis (FMECA), reliability block diagrams (RBD), Markov models, fault tree analysis, Petri nets, Poisson processes, Bayesian models, and Monte Carlo methods. Among these, RBD was the most widely used tool for system, subsystem or component performance modeling technique, while functional analysis and FMEA/FMECA were the most common descriptive methods. A critical gap was identified in validation practices, with few studies incorporating validation procedures. Corrective maintenance was identified as the dominant maintenance strategy. Sensitivity analysis was frequently performed, with input parameter sensitivity being the most commonly applied approach. Most studies relied on third-party databases for input data. The findings also highlight the widespread adoption of RAM + analysis across multiple industries, with nuclear fusion emerging as the most prominent application domain. RAM + methodologies are often applied in hybrid approaches, demonstrating their adaptability to diverse engineering challenges. Research limitations/implications A critical gap was identified in validation practices, with a few studies incorporating validation procedures. Corrective maintenance was identified as the dominant maintenance strategy. Sensitivity analysis was frequently performed, with input parameter sensitivity being the most applied approach. Practical implications The findings also highlight the widespread adoption of RAM + analysis across multiple industries, with nuclear fusion emerging as the most prominent application domain. RAM + methodologies are often applied in hybrid approaches, demonstrating their adaptability to diverse engineering challenges. This review underscores the importance of RAM + analysis in assessing system performance and safety parameters while identifying risk-based improvements. The insights, gaps, and tendencies identified serve as foundation for future improved research studies and applications in this topic. Originality/value This study presents a systematic literature review (SLR) on reliability, availability, maintainability (RAM) analysis methodologies and derivations (especially RAMI, RAMS, and RAMSS), their applications, and research gaps across several engineering domains.