In order to maintain competitiveness, it is imperative for the oil and gas sectors to consistently enhance the effectiveness and efficiency of their production methodologies. The aforementioned circumstances have heightened apprehensions regarding equipment accessibility and the imperative for efficient maintenance. Within this particular context, the primary obstacle encountered by previous research endeavors is the selection of the most appropriate maintenance strategy. The strategic methodology for incorporating reliability, availability, and maintainability (RAM) is hindered in its ability to achieve productive objectives due to the utilization of techniques, tools, and technical engineering practices. These practices, such as mean time to failure, equipment downtime, and system availability values, are commonly employed to evaluate the reliability of the plant. This paper examines the utilization of RAM analysis in the context of oil refinery plants, employing it as a case study. The assessment of the system's reliability was conducted through the utilization of the reliability block diagram (RBD), which facilitated the identification of critical components. Following that, an examination was conducted to assess the availability and the effects of various maintenance strategies on the refinery. This examination involved the implementation of corrective maintenance (CM) as well as corrective and preventive maintenance (CM & PM). The Reliability Block Diagram (RBD) was simulated over a period of 365 days, equivalent to 8760 hours. The outcome of the simulation revealed an availability rate of 90. The results obtained from the RBD analysis were compared to the strategies of Condition Monitoring (CM) and Condition Monitoring and Preventive Maintenance (CM & PM) implemented in the refinery. The availability achieved using the CM method was 72.79, whereas the combined use of CM and PM resulted in an availability of 91.91. The findings demonstrate that the implementation of CM & PM significantly affects the availability of the plant, leading to reduced equipment downtime in comparison to the results obtained from the RBD analysis. © 2024 Author(s).