With the increasing complexity of medical equipment, traditional quality control methods are facing great challenges. This paper proposes a gridded quality control strategy based on big data analytics, which realizes accurate management of medical equipment through data collection and analysis, dynamic monitoring and intelligent early warning, fault prediction and optimization. Experiments show that this strategy is effective in improving the accuracy of equipment failure prediction and optimizing facility management.