作　　者： ; ;

机构地区： 暨南大学经济学院统计学系

出　　处： 《数理统计与管理》 2006年第3期335-340,共6页

摘　　要： 常规统计控制图的基本假设前提是观测值独立同分布,而在实际生产过程中,质量指标值常表现出自相关现象,违背独立性假定。本文运用平均链长(ARL)研究自相关过程为AR(1)时对常规控制图的影响,并比较了常规控制图和残差控制图对序列相关过程的控制效果。模拟结果和实例分析表明:当过程序列相关时,使用常规作图法估计出的标准差是有偏的,致使控制限设置错误和常规控制图检测能力降低。因此,在一些统计过程控制中,须考虑自相关现象并采用适当的控制图方法。 Traditional statistical process control charts assume that observations are independent and identically distributed. However, autocorrelated effects are often substantial in manufacturing processes and the assumption of independence is violated. In the paper, we investigate the effects of autocorrelation on traditional control chart when the correlation can be described by an AR（ 1 ）model. We compare the performance of the Shewhart chart to the performance of the residual chart. The measure of performance used is the average run length. The results show that the usual estimator for the standard deviation is biased in case of corelated observations. Consequently, the control limits are not correctly and the detection capability of traditional control charts is reduced. So methods for dealing with autocorrelated data in the statistical process control environment have been considered.

关 键 词： 自相关过程 控制图 平均链长 模拟研究

领　　域： [理学] [理学]