摘要
针对参数随机化情况下生产过程能力的评价问题,提出了新的过程能力指数估计与评价方法。通过质量控制模型的统计结构分析,研究了扩散先验分布下参数后验分布,据此构造了过程能力指数的贝叶斯点估计和区间估计;在此基础上,将前一阶段模型参数后验分布作为下一阶段的参数先验分布,充分利用历史数据信息,建立了过程能力指数及其下限的贝叶斯动态评价模型。研究结果表明:与现有的贝叶斯过程能力指数估计方法比较,贝叶斯动态过程能力指数的预测精度优于前者,更能反映实际生产过程能力水平。
To analyze the process capability under random parameters, a new kind of process capability index is designed in this paper. Based on the statistical model for quality variables, we explored the parameters ＇ Bayesian point estimates and interval estimation with a diffuse prior and developed a Bayesian process capability index. Then, we considered the parameters＇ current posterior distribution to be their prior distribution in the next phrase when the process is capable, by which the Bayesian dynamic process capable index is established. Finally, we give an example to show how to use the method proposed in this paper. The results indicate that the accuracy of estimators for process capability indices can be improved through Bayesian dynamic statistical methods.
出处
《中国管理科学》
CSSCI
北大核心
2009年第4期170-177,共8页
Chinese Journal of Management Science
基金
国家自然科学基金项目(70770138)
教育部新世纪人才支持计划项目(NCET050704)
关键词
质量控制
过程能力指数
贝叶斯方法
估计
先验分布
quality control
process capability index
bayesian method
estimation
prior distribution
