The nuclear safety-class Distributed Control System (DCS) plays a pivotal role in maintaining the safe and stable operation of nuclear power plants. To enhance the quality of safety-class DCS, this study employs reliability analysis as the foundation, integrating tools such as FMEA (Failure Mode and Effects Analysis), dynamic fault trees, Markov models, and decision tables. For each potential failure mode of safety-class DCS equipment, the potential impacts of failure are analyzed. A dynamic reliability analysis model is established from the perspective of critical functions such as reactor trip and engineered safety feature actuation. By analyzing the dynamic model, the failure rate is calculated layer by layer following a bottom-up logic. A decision table is utilized to consolidate key information, including significance, optimization potential, and failure rates derived from the model analysis, thereby identifying vulnerabilities in critical functional chains. Corresponding design improvements are then implemented through technical measures to enhance the quality of the safety-class DCS. This approach ensures a systematic and rigorous reliability assessment, ultimately contributing to the robustness and dependability of nuclear power plant safety systems.