This study proposes a maintenance task decision-making method that integrates FMEA, RCM, and PHM. An FMEA failure risk assessment model is established in accordance with EN 50126 to quantify failure risks and determine risk grades across three dimensions: failure severity, occurrence frequency, and detectability. Reliability-centered maintenance analysis is implemented to screen critical maintenance items, analyze functional failures, classify failure impacts, and make logical decisions about maintenance tasks, thereby forming standardized maintenance tasks. Combined with PHM technology, maintenance strategies are optimized based on a matrix of failure impact and occurrence frequency; candidate items for PHM construction are selected with priority defined; and an integrated maintenance decision-making system covering risk assessment, reliability decision, and intelligent health management is ultimately established. Full-process verification is performed with the IGBT module, the core component of traction systems, as the research object. The results reveal that the proposed method reduces the risk level of IGBT modules from unacceptable to acceptable and extends the tertiary maintenance mileage from 1.2 million km to 1.6 million km, effectively improving the economic efficiency and intelligence of equipment operation and maintenance. The hybrid-driven decision-making methodology establishes a progressive closed-loop framework of FMEA - RCM - PHM - RCM. By leveraging a unified risk quantification value as the linking bridge, it achieves the integrated fusion of the three approaches. This provides both theoretical support and practical engineering reference for optimizing maintenance systems and constructing intelligent operation and maintenance frameworks for railway vehicle traction systems.