A RAM-C Based Approach for Determining the Optimal Operational Plan of Drone Weapon Systems

• 해당 논문은 APIC-IST 2025에서 발표되었습니다.

Gahyun Kim and Ki-young Lee

모아소프트㈜

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Key Words : RAM-C Analysis, Operational Profile, Reliability, Availability, Life Cycle Cost

서론

This study aims to determine the optimal operational concept for a military cargo drone by applying the RAM-C (Reliability, Availability, Maintainability, and Cost) analysis methodology. Three operational scenarios were established based on mission distance and frequency, and a comparative analysis was conducted using key RAM elements such as MTBF, operational availability (Ao), and life cycle cost (LCC). The results derived from SIMLOX simulations revealed trade-offs among the RAM elements, particularly between Ao and LCC. Based on these findings, the study confirms that RAM-C analysis can serve as a practical decision-making tool for the development of drone operation policies and the optimization of maintenance support systems.

…중략

결론

This study aimed to identify the optimal operational concept for military cargo drones by comparing performance and cost factors under different operational scenarios using the RAM-C analysis framework. The results showed that the optimal operational mode should be determined not simply by mission intensity, but by considering its connection to support systems such as maintenance efficiency and spare parts availability.

Although MTBF values were similar across all scenarios, there were clear differences in operational availability and life cycle cost. Scenario C, with the highest mission frequency, achieved high availability with a moderate LCC, while Scenario B (long-range transport) showed the lowest availability and the highest LCC, highlighting the impact of asset utilization efficiency and maintenance burden on performance.

In the future, the RAM-C based evaluation method proposed in this study could be applied to various types of weapon systems, operational environments, and maintenance strategies. It is expected to serve as a practical and quantitative decision-making tool for optimizing military support systems and implementing performance-based logistics (PBL) policies.