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一种基于产出合格率的过程能力指数及其置信下限的估计
引用本文:田志友,田澎,王浣尘.一种基于产出合格率的过程能力指数及其置信下限的估计[J].工业工程与管理,2004,9(6):41-44,60.
作者姓名:田志友  田澎  王浣尘
作者单位:上海交通大学,安泰管理学院,上海,200052
摘    要:介绍了一种基于加工过程产出合格率的过程能力指数Cpc,并推导了Cpc指数与过程合格率之间的弹性系数。指出:相对于传统过程能力指数来说,Cpc计算简单,含义明确,不受过程分布特性的影响,可适用于双边或单边规格限情况,尤其是Cpc指数相对产出合格率非常富于弹性,可以有效反映过程质量的波动情况。为了获得Cpc,指数的概率分布及相关统计推断,利用Bootstrap抽样技术,对Cpc样本估计量的分布情况进行仿真处理,得到Cpc的经验分布及其置信下限,为更有效的使用该指数提供了概率依据。最后对Cpc指数的具体应用给出了案例分析。

关 键 词:过程能力指数  产出合格率  置信下限  Bootstrap抽样
文章编号:1007-5429(2004)06-0041-04

A Process Capability Index Based on the Proportion of Conformanceand the Estimation of Its Lower Confidence Limit
TIAN Zhi-you,TIAN Peng,WANG Huan-chen.A Process Capability Index Based on the Proportion of Conformanceand the Estimation of Its Lower Confidence Limit[J].Industrial Engineering and Management,2004,9(6):41-44,60.
Authors:TIAN Zhi-you  TIAN Peng  WANG Huan-chen
Abstract:A new kind of process capability index (PCI) named C_(pc) was introduced, which was derived based on the proportion of conformance of the process. The elastic coefficient between C_(pc) and the proportion of conformance was deduced too. It is pointed out compared with the traditional PCIs, the C_(pc) index was more straightforward in its assessment and interpretation, immune to the distributing characteristics of the process, and could be used with either unilateral or bilateral specifications. Moreover, the C_(pc) index was very elastic when related to the proportion of conformance, which indicated its effectiveness in reflection of the quality fluctuation. To acquire the stochastic distribution and related statistical inferences of C_(pc), this paper simulated the distribution of the estimated statistic for C_(pc) with the bootstrap sampling method and got the empirical distribution for C_(pc). Its lower confidence limit could provide the basis of probability for more effective uses of that index. In the end, a case analysis was given for the concrete applications of the C_(pc) index.
Keywords:process capability indices  proportion of conformance  lower confidence limit  bootstrap sampling
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