Integrating Repair Modes into RAMS for Enhanced System Reliability

This paper introduces a novel extension to traditional RAMS methodology by incorporating repair modes, distinct classes of corrective interventions, as a critical factor in system reliability and maintainability modeling. While failure modes are well-established in RAMS analyses, repair actions are often aggregated, leading to inaccurate availability predictions. Using operational data from 19 oil wells in a South American field, we identify three statistically distinct repair modes: minor interventions (3,000 hours). Each mode is modeled with a separate distribution (lognormal for repair times; Crow-AMSAA for failure intensity), integrated into a unified RAMS simulation framework. Validation via Monte Carlo methods confirms that ignoring repair mode diversity results in significant underestimation of downtime and overestimation of production. This approach enhances predictive accuracy for asset management and maintenance planning in complex industrial systems.