高质量产品的可靠性监控与数据分析技术研究

This research proposal has been developed against the backdrop of China’s government unveiling the grand strategic scheme “Made in China 2025”—the blueprint for future development and growth for China’s manufacturing industry. The proposal is primarily focused on the real problems faced in high-quality manufacturing practices—difficulties and challenges in reliability monitoring and data analysis for high-quality products. By using statistical quality control, reliability modelling and Bayesian analysis, this proposal is aimed at developing theoretically sound, effective and useful methods and techniques for practitioners in the high-quality manufacturing industry. The three major topics proposed are: 1) reliability monitoring techniques for high-quality products; 2) reliability analysis methods under data scarcity; 3) Bayesian approaches for reliability analysis under data scarcity. The proposed research will be able to contribute valuable new methods and techniques to the quality control practices in the high-quality manufacturing industry, if successfully funded.

本课题以《中国制造2025》国家战略的推动实施和中国制造业的转型升级为背景，立足于高质量制造业的生产实践，综合运用统计质量控制、可靠性理论、贝叶斯统计等领域的方法和技术，针对高质量产品的可靠性监控与数据分析所面临的实际问题，探索理论稳健、实用有效的解决方法和技术。具体内容分三个专题展开：第一，高质量产品的可靠性监控技术；第二，数据稀缺条件下的可靠性分析技术；第三，数据稀缺条件下的可靠性分析的贝叶斯方法。研究内容具有前瞻性、创新性和学科交叉等特点。预期的研究成果能为高质量制造业的质量与可靠性管理提供实用的技术和方法，为中国制造业迈向高质量制造做出贡献。

本课题立足于高质量制造业的生产实践，针对高质量产品的可靠性监控与数据分析所面临的实际问题，提出了理论稳健、实用有效的解决方法和技术。具体内容包括三个专题：1）高质量产品的可靠性监控技术；2）数据稀缺条件下的可靠性分析技术；3）数据稀缺条件下的可靠性分析的贝叶斯方法。目前，在三个专题研究上，均取得了重要或突破性进展，相关研究成果已经发表在本领域国际一流期刊，得到了同行的认可和肯定。项目所开发出的分析方法和技术能解决生产实践中的真实问题，具有良好的理论和应用价值。