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基于多阶段抽样的贝叶斯序贯过程质量监控分析 被引量:4

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摘要 文章针对参数随机化情况下的质量控制问题,提出了新的过程质量方法。通过质量控制模型的统计结构分析,研究了Jeffreys先验分布下参数的后验分布和贝叶斯估计,据此构造了具有预警线的过程样本均值-标准差监控图,以及贝叶斯过程能力指数评价模型;然后,将过程状态稳定的模型参数后验分布作为下一阶段的参数先验分布,进行样本数据信息融合、模型迭代更新,建立了基于共轭先验分布的贝叶斯序贯均值–标准差监控和贝叶斯动态过程能力指数估计模型。研究结果表明:与现有的统计过程质量控制方法比较,贝叶斯序贯过程质量监控方法能够融合产品质量指标的历史信息,及时更新过程控制限,动态监控过程质量波动。
出处 《统计与决策》 CSSCI 北大核心 2010年第8期8-12,共5页 Statistics & Decision
基金 国家自然科学基金资助项目(70771038) 教育部新世纪优秀人才支持计划项目(06JA910001)
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参考文献16

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二级参考文献9

共引文献2

同被引文献41

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