Complex systems, such as Nuclear Power Plants (NPPs) require regular and effective maintenance to ensure their safety and reliability. Selecting an optimal maintenance strategy is challenging, because it must balance multiple, often conflicting criteria, including reliability, safety, and cost. This study proposes a maintenance optimization framework based on Fault Tree Analysis (FTA) and importance indexes, with a particular focus on sensitivity to mission time and failure probability distribution. The framework is demonstrated on the Chemical Volume Control System (CVCS), a vital subsystem of Pressurized Water Reactors (PWRs). Using FTA, 176 cut sets were identified, including 11 first-order cut sets where a single component failure (e.g., regenerative heat exchanger, motorized valve 4, check valve 1) could cause system failure. Quantitatively, for a 90 day mission time, 10 components exceeded ASME thresholds (FV > 0.005, RAW > 2), requiring prioritized inspection, whereas for a 30 day mission time, no components required immediate maintenance. These results demonstrate that maintenance recommendations are highly sensitive to both mission time and the assumed failure probability distribution. Unlike previous studies that applied FTA and importance indexes without systematically addressing this sensitivity, the present work explicitly quantifies these effects, thereby filling a critical research gap and providing an operationally realistic basis for maintenance optimization in PWR systems.
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