In modern manufacturing, quality management is crucial for ensuring products meet customer requirements and industry standards. Traditional quality inspection systems face limitations in data collection, analysis, and sharing. This paper presents a cloud-based quality inspection information management system designed to enhance inspection efficiency and accuracy, enable real-time data sharing and analysis, and reduce maintenance costs. The system integrates three-tier and microservices architecture with cloud computing and big data technologies to achieve real-time data collection, storage, and analysis. Key features include data collection and processing, real- time monitoring and alerting, data analysis and visualization, and system integration. Security and reliability are ensured through multi-layer data encryption, access control, and fault tolerance mechanisms. The paper concludes by summarizing the research outcomes and identifying future improvements, including deep learning for quality prediction, blockchain for traceability, edge computing, and intelligent operations. This system aims to provide an efficient, reliable, and secure solution for quality management in manufacturing, enhancing overall quality and competitiveness.