• 목록

The Republic of Korea Navy currently employs MTBF-based periodic maintenance, which fails to reflect lifecycle-based failure rates. This study proposes a digital twin-based predictive maintenance framework and examines its policy and technical foundations. As smart factory initiatives and early-stage digital twin integration expand, a shift toward condition-based maintenance (CBM) is becoming more feasible. PdM has shown practical benefits in aerospace and manufacturing industries, including reduced failure rates, lower maintenance costs, and increased equipment uptime. Furthermore, GCN-based time-series anomaly detection is gaining attention as a key diagnostic tool. This paper highlights PdM’s applicability to naval systems and its potential to improve availability and efficiency.