可变样本容量和抽样区间的联合中位值和极差控制图

最近的理论研究表明具有可变样本容量(VSS)和可变抽样区间(VSI)的控制图比常规控制(FSSI)图能更快地揭露生产过程中的问题．本文将以前单个控制图的研究方法推广到联合中位值(x^-)和极差(R)控制图，记作CVSSIx^-—R图．假定过程处于控制状态的时间T服从负指数分布。利用Costa的马氏链方法设计CVSSIx^-—R图。并同联合常规(CFSSI)图作比较．所设计的CVSSI图较之CFSSI图能更快地发现过程平均值和方差的较小和中等的变化，从而减小不合格品数．     

可变样本容量和抽样区间的联合和R控制图

作者在前文[1] 中研究了可变样本容量 (VSS)和抽样区间 (VSI)的中位值 (～x)和极差 (R)控制图 ,指明其功效均大于常规 (FSS)控制图。本文将前文的研究方法推广到联合 ～x 和R图 ,记作CVSSI～x -R图 ,它能更快地发现过程平均值和方差的变化 ,从而减少不合格品数     

在固定时间抽样的可变抽样区间控制图

本文根据Reynolds在固定时间抽样的可变抽样区间（VSIFT）的x^-控制图^[1]的模型设计中位值x^-和极差R图，规定样本在样等间隔的固定时间点抽取，当过程有变化的迹象时，允许有两个固定时间之间抽取附加样本，本文计算了VSIFTx^~图和R图及联合x^~-R图的发信号前的平均时间，并同固定抽样区间（FSI）的常规x^~和R图作比较，所设计的VSIFTx^~和R图能缩短过程失控时间从而减少不合格品数。     

可变抽样区间的单边控制图

利用质量控制图监督生产过程时 ,通常每隔固定时间从过程抽取固定容量的样本。本文在前文[1] 的基础上设计具有可变抽样区间的单边标准差 (S)图、极差 (R)图和不合格品数 (np)图。计算了这三个图发信号前的平均样本数和平均时间 ,并同固定抽样区间的常规控制图作比较。所设计的控制图能缩短过程失控时间从而减少不合格品数。     

具有可变抽样区间的EWMA标准差控制图

对指数加权滑动平均即EWM A标准差控制图进行了可变抽样区间设计,用M arkov-cha in方法给出了该控制图的平均报警时间的计算公式,并同固定抽样区间的常规EWM A标准差控制图进行比较,数据显示,所设计的控制图能较快的发现过程变化从而减少产品的不合格率.     

具有可变抽样区间的Poisson EWMA控制图

传统的EWMA控制图通常都是针对计量型质量特性值的,而对于计数型质量特征值少有研究.设计了单位缺陷数服从Poisson分布的EWMA控制图,并对Poisson EWMA控制图进行了可变抽样区间设计,利用Markov chain方法计算了其平均报警时间,计算结果表明,所设计的动态Poisson EWMA控制图较Shewhart c-图和固定抽样区间的Poissin EWMA控制图能更好的监控过程的变化.     

在固定时间抽样的可变抽样区间的极值控制图

本文根据 Reynolds在固定时间抽样的可变抽样区间 (VSIFT)的 - x控制图 [1 ]的模型设计极值 (ζ)图。规定样本在相等间隔的固定时间点抽取 ,当过程有变化的迹象时 ,允许在两个固定时间之间抽取附加样本。若样本点超过控制限 ,则 VSIFT图同常规图一样发信号。本文计算了 VSIFTζ图的发信号前的平均时间 ,并同固定抽样区间 (FSI)的常规ζ图作比较。极值图不需计算 ,有关集中和分散的信息在一个图上给出 ,且可画上规格限 ,在实践中应用方便。本文设计的 VSIFTζ图能缩短过程失控时间从而减少不合格品数     

可变抽样区间的累积合格品数控制图

本文提出了可变抽样区间的累积合格品数控制图.计算了它的发信号前平均时间,并同固定抽样区间的累积合格品数控制图进行了效率比较.     

可变抽样区间的二项EWMA控制图

在制造过程中,对产品的不合格品数进行监控时,通常选用计数性控制图-np图,它是基于过程服从二项分布建立的,一般对于过程中出现的较大波动效果明显。为了提高控制图对不合格品数较小波动的监控效果,本文设计了产品不合格品数服从二项分布的EWMA控制图。提出可变抽样区间的二项EWMA控制图,并采用马可夫链法计算其平均报警时间。对固定抽样区间以及可变抽样区间二项EWMA控制图对比研究,表明当过程失控时,可变抽样区间二项EWMA控制图具有较小的失控平均报警时间,能够迅速监测出过程中的异常波动,明显优于固定抽样区间的二项EWMA控制图。     

可变抽样区间同时监控均值标准差的EWMA控制图

传统的EWMA控制图分别针对监控过程均值变化和监控过程标准差变化进行研究,在实际生产中,很多情形需要同时监控过程均值变化和过程标准差变化。为了提高控制图的监控效率,本文研究了同时监控均值和标准差变化时,EWMA控制图的可变抽样区间设计。其次运用马科夫链法计算可变抽样区间EWMA控制图的平均报警时间;然后与传统的EWMA控制图进行比较得出:同时监控均值和标准差时,可变抽样区间的EWMA控制图能够更快地发现过程中的异常波动,具有较短的平均报警时间,其监控效率明显优于传统的EWMA控制图。     

Cumulative conformance count chart with variable sampling intervals and control limits

The cumulative conformance count (CCC) chart has been used for monitoring processes with very low fraction of nonconforming items. Typically, the items produced from the process were examined using 100% inspection for generating the CCC chart. However, this would be costly when taking the inspection cost and time into consideration and thus limit its application. Instead of inspecting the items one by one, this study takes sample from them, and regards the time between two successive samples as the sampling interval. In order to increase the sensitivity of the CCC chart to process change, the sampling interval and control limits are allowed to vary in this study. The average time to signal process change of the modified CCC chart (called the variable sampling interval and control limit (VSI/VCL) CCC chart) is derived by the Markov chain approach and taken as the performance measure to evaluate its statistical efficiency. With some minor changes, this chart can be reduced to the VSI CCC chart, the VCL CCC chart, and the standard CCC chart. In addition, comparisons among them are made and discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Steady-state-optimal adaptive control charts based on variable sampling intervals

Variable sampling interval (VSI) control charts vary the sampling rate adaptively as a function of the data coming from the process in order to reduce the detection delay of process changes. Zero-time performance refers to the detection delay of a process change that is present during the onset of the chart at time zero. Steady-state performance refers to the detection delay of a process change that occurs after the chart has been operating for some time. The zero-time performance of a VSI control chart can differ considerably from the chart's steady-state performance, which is generally more important than the zero-time performance. We develop an efficient quadratic-programming algorithm for the construction and investigation of steady-state-optimal sampling policies for various VSI charts. We show that a steady-state-optimal VSI scheme is fundamentally different from the respective zero-time-optimal VSI scheme, and recommend VSI policies based on two sampling intervals for the various types of control charts considered.     

Variable sampling interval Shewhart control charts for monitoring the multivariate coefficient of variation

In many industrial manufacturing processes, the ratio of the variance to the mean of a quantity of interest is an important characteristic to ensure the quality of the processes. This ratio is called the coefficient of variation (CV). A lot of control charts have been designed for monitoring the CV of univariate quantity in the literature. However, the CV control charts for multivariate quantity have not received much attention yet. In this paper, we investigate a variable sampling interval (VSI) Shewhart control chart for monitoring multivariate CV. The time between two consecutive samples is allowed to vary according to the previous value of the multivariate CV, which will help the chart to detect the process shifts faster. The comparison with the fixed sampling interval Shewhart chart is implemented to highlight the advantage of the VSI method. Finally, an illustrative example is demonstrated on real data.     

基于可变抽样区间的累积和方差控制图研究

介绍了基于对数方差的累积和控制图,进行了可变抽样区间的控制图设计用Markov链方法计算可变抽样区间的累积和方差控制图的平均报警时间,并且与固定抽样区间的控制图进行比较,分析在不同参数取值下的平均报警时间.     

Adaptive sampling enhancement for Hotelling’s T charts

This paper makes a study of an adaptive sampling scheme useful to increase the power of the fixed sampling rate (FSR) T² control chart. In our study, the three parameters of T² control chart: the sample size, the sampling interval, and the upper percentage factor that is used for determining the action limit, vary between two values for a relaxed or tightened control, depending on the most recent T² value. The average time to signal (ATS) and adjusted average time to signal (AATS) a shift in the process mean vector for the new chart are derived and regarded as an objective function respectively to optimize its design parameters. With some minor changes, the new chart can be reduced to the variable sampling interval (VSI) T² chart, the sample size (VSS) T² chart, the variable sample size and sampling interval (VSSI) T² chart, or the FSR T² chart. Numerical comparisons among them are made and discussed. Furthermore, the effects of the initial sample number (use for estimating the in-control process parameters) upon the chart’s performance and adaptive design parameters are presented.     

固定时间域可变采样间隔的统计控制图

本文从提高统计控制图对过程波动检测能力和方便管理的角度出发 ,对可变采样间隔(VSI)控制图进行改进 ,提出了针对连续过程质量控制应用需要的固定时间域可变采样间隔(VSIFT)控制图。文章详细介绍了VSIFT均值极差控制图、VSIFTEWMA控制图的设计 ,并分别评价了它们对过程异常状态的检测能力