带警戒限的合格品链长控制图

研究了两种带警戒限的合格品链长控制图,一种是一个链长控制图,另一种是两个链长控制图.首先,给出了这两种控制图的制定方法;其次,利用概率流图方法得到了这两种控制图的平均链长(ARL)的计算公式;最后,推导了它们效率的度量指标ANI(发信号之前的平均检验的样品数)的计算公式.     

合格品链长控制图

在生产过程中不合格品率(p)很低的情况下,利用两个连续不合格品之间的合格品数(合格品链长)控制图来监督过程不合格品率能克服传统的p图所遇到的困难,为生产者提供产品质量改良的信息。本文研究两种合格品链长(CRL)控制图的制定方法,对这些控制图的效率进行了比较,并说明其实际应用。所研究的CRL控制图特别适用于自动化生产过程的100%检验的质量控制。     

单边合格品链长中位数控制图设计

针对过程数据存在异常值的问题,为了监控过程均值的偏移,采用中位数统计量(X)代替传统均值(X)统计量,提出了一种单边合格品链长X(Sided Sensitive Conforming Run Length X, SCRL & X)控制图。采用马尔科夫链方法研究了SCRL & X控制图的性能,首先推导出其一步状态转移矩阵,进一步根据马尔科夫链的性质得到其平均链长(Average Run Length, ARL)。为了获得控制图的最优设计参数和性能指标值,保证其处于过程受控状态下的性能,并使其处于过程失控状态下的平均链长最小。研究结果表明,提出的SCRL & X控制图的统计性能优于传统的双边合格品链长X(Conforming Run Length, CRL & X)控制图,尤其针对过程均值产生较小偏移的情形,其优势较为明显。     

基于未知分布的均值和方差的稳健EWMA图

研究了当待监控质量特性所服从的分布类型和分布参数未知时的EWMA控制图的构建问题。通过仿真分析对几种分别用于监控过程均值和过程方差的EWMA控制图方法的运行长度进行比对,用以评价控制图的效率以及对未知分布的稳健性,根据效率评价的结果获得了适用于分布未知情况下的均值和方差的稳健EWMA控制图。最后分别提出了这两种均值和方差的稳健EWMA图的优化设计方法.     

复杂机电产品多元FT VSI贝叶斯控制图性能研究

针对复杂机电产品质量控制与预警困难的问题,构建一种将多元贝叶斯统计方法与经济性能分析相结合的多元贝叶斯控制图性能分析模型.在求解模型中,多元贝叶斯控制图采用固定时间变抽样区间(Fixed Time Variable Sample Interval, FT VSI)策略,若非随机故障小概率发生,则选择宽松抽样方案;若非随机故障大概率发生,则选择严抽样方案.为量化多元贝叶斯控制图经济性能与统计性能的相关度,利用蒙卡罗模拟分析的质量控制模型进行仿真,并在不同经济性参数下,得到采样单位平均数(Average Number of Observations to Signals or End of the production run, ANOSE)对于控制图统计性能的影响程度,进而引出多元贝叶斯控制图的质量控制成本与其误报率的影响程度,并以某型号汽车自动变速器多元质量控制过程为例对多元FT VSI贝叶斯控制图性能评价与优化成果进行验证,结果证明该方法具有较好的应用性.     

修正贝叶斯控制图与累积和控制图的比较分析

面向多品种、小批量制造过程的小波动检验是目前统计过程控制图发展和研究的方向.在对修正贝叶斯控制图与累积和控制图原理进行比较后,通过一组过程仿真数据对两种控制图进行了分析,指出了两种控制图的特性和应用前景.     

改进型单边EWMA指数控制图设计

现代制造过程中,某些产品的不合格率非常低,通常将这类过程称为高质量过程。由于高质量过程中相邻不合格产品之间的时间间隔服从指数分布,可以通过指数控制图实现对过程状态的监控。因此,本文提出一种改进型指数加权移动平均(Improved Exponentially Weighted Moving Average,IEWMA)指数控制图,并采用蒙特卡洛仿真获得控制图的平均运行链长(Average Run Length,ARL),仿真结果表明该控制图的性能优于传统单边EWMA指数控制图,尤其针对过程中产生较小偏移的情形具有较好的检测性能。     

基于APL的EWMA控制图经济统计优化设计

为了提高指数加权移动平均(EWMA)控制图监控效率评价的精确性和全面性,提出用一个质量周期内的平均产品个数替代平均抽样个数来进行控制图的经济性和统计性综合评价,建立了一种基于平均产品长度(APL)的更为精确的EWMA控制图经济统计多目标优化设计模型,并采用具体的算例说明了采用NSGA-Ш算法对该模型进行计算的步骤。最后,用该方法优化设计的EWMA控制图与已有的几种EWMA控制图优化设计进行比较,结果表明:本文提出的经济统计优化设计方法显著优于只考虑经济性能的经济设计和只考虑统计性能的统计设计方案。     

图的可定向嵌入的标根可数性

给定一族图G,可定向曲面上存在多少个以其中某个图为基础图的标根地图？采用图的自同构群对图在可定向曲面上的嵌入集合进行分类，该文解决了这个问题，同时得到了求解计数函数f^r(M)的一种新的方法。     

自相关过程的改进型EWMA控制图

常规指数加权移动平均(EWMA)控制图的假设前提是观测数据相互独立,但在实际生产过程中,数据相关违背假设条件。本文首先讨论了序列自相关对常规EWMA控制图的影响,结果表明其检测效能降低。因此,重新估计了平稳过程的σz并在此基础上建立了改进型EWMA控制图。然后运用平均链长比较了改进型EWMA控制图与休哈特图和残差控制图,模拟研究说明当过程非强相关且过程均值发生中小偏移条件下。改进型EWMA控制图的检测效果要优于其他两种控制图。最后,通过一个实例验证了该方法的有效性。     

自相关过程的残差控制图

由于自相关过程违背了过程输出数据独立性的假定,使得传统休哈特图的有效性受到质疑。本文首先讨论控制图设计基本思想,然后分析了对自相关过程监控的残差控制图原理;进而以平均链长和各链点检出概率为准则,系统研究了AR(1)过程残差控制图的检测能力,并与休图进行了比较。最后,通过一个模拟验证了该方法的有效性。     

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.     

基于主成分原理的多元质量控制图的构造

控制图是从事统计质量管理经常使用的重要工具,经过多年的发展和实践,一元质量控制图业已得到普遍推广,可是如何开展多元质量控制仍有许多问题值得探讨。在这篇文章中,我们着重讨论了基于主成分分析的多元质量控制图的构造,并结合从企业现场采集到的数据给出了具体的应用说明。     

Optimization designs and performance comparison of two CUSUM schemes for monitoring process shifts in mean and variance

In statistical process control (SPC), when dealing with a quality characteristic x that is a variable, it is usually necessary to monitor both the mean value and variability. This article proposes an optimization algorithm (called the holistic algorithm) to design the CUSUM charts for this purpose. It facilitates the determination of the charting parameters of the CUSUM charts and considerably or significantly increases their overall detection effectiveness. A single CUSUM chart (called the ABS CUSUM chart) has been developed by the holistic algorithm and fully investigated. This chart is able to detect two-sided mean shifts and increasing variance shifts by inspecting the absolute value of sample mean shift. The results of performance studies show that the overall performance of the ABS CUSUM chart is nearly as good as an optimal 3-CUSUM scheme (a scheme incorporating three individual CUSUM charts). However, since the ABS CUSUM chart is easier for implementation and design, it may be more suitable for many SPC applications in which both mean and variance of a variable have to be monitored.     

Economic design of an attribute control chart for monitoring mean life based on multiple deferred state sampling

In this paper, we design an attribute np control chart using multiple deferred state (MDS) sampling under Weibull distribution based on time truncated life test. This chart is constructed for monitoring the variation of mean life of the product in a manufacturing process. The optimal parameters of MDS sampling and the control limit coefficients are determined so that the in‐control average run length (ARL) is as close as to the target ARL. The optimal parameters of MDS sampling are sample size and number of successive subgroups required for declaring the current state of process. Out‐of‐control ARL is considered as a measure of the performance of proposed chart and reported with determined optimal parameters for various shift constants. The out‐of‐control ARL of the proposed chart obtained under various distributions is compared with each other. The performance of proposed control chart is compared with the performance of the existing control chart designed under single sampling. In addition, the economic design of proposed chart using variable sampling interval scheme is discussed, and sensitivity analysis on expected costs is also investigated.     

Control charts based on randomized quantile residuals

In practice, quality characteristics do not always follow a normal distribution, and quality control processes sometimes generate non‐normal response outcomes, including continuous non‐normal data and discrete count data. Thus, achieving better results in such situations requires a new control chart derived from various types of response variables. This study proposes a procedure for monitoring response variables that uses control charts based on randomized quantile residuals obtained from a fitted regression model. Simulation studies demonstrate the performance of the proposed control charts under various situations. We illustrate the procedure using two real‐data examples, based on normal and negative binomial regression models, respectively. The simulation and real‐data results support our proposed procedure.     

Hotelling’s T charts with variable sample size and control limit

The ideas of variable sampling interval (VSI), variable sample size (VSS), variable sample size and sampling interval (VSSI), and variable parameters (VP) in the univariate case have been successfully applied to the multivariate case to improve the efficiency of Hotelling’s T² chart with fixed sampling rate (FSR) in detecting small process shifts. However, the main disadvantage in using most of these control schemes is an increasing in the complexity due to the adaptive changes in sampling intervals. In this paper, retaining the lengths of sampling intervals constant, a variable sample size and control limit (VSSC) T² chart is proposed and described. The statistical efficiency of the VSSC T² chart in terms of the average time to signal a shift in process mean vector is compared with that of the VP, VSSI, VSS, VSI, and FSR T² charts. From the results of comparison, it shows that the VSSC T² chart for a (very) small shift in the process mean vector gives a better performance than the VSSI, VSS, VSI, and FSR T² charts; meanwhile, it presents a similar performance to the VP T² chart. Furthermore, from the viewpoint of practicability, it is more convenient for administrating the control chart than the VSI, VSSI, and VP T² chart. Thus, it may provide a good option for quick response to small shifts in a multivariate process.     

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Aiming at the complex mechanical and electrical products quality control and early warning problems, a performance analysis model of control chart, which combines the multivariate Bayesian statistical method with the economic performance analysis is constructed. In the solution model, a FT VSI strategy is used in the multivariate Bayesian control chart. If a small probability of random failure occurs, then a loose sampling scheme is selected. Otherwise, a strict sampling program is applied. To quantify the correlation between the economic and the statistical performance of the multivariate Bayesian control chart, a quality control model based on Monte Carlo simulation is used and the ANOSE (Average Number of Observations to Signals or End of the production run) is taken under different economic parameters, which performs the degree of influence of the statistical performance of the control chart. In addition, the relationship between the quality control cost and the false alarm rate of the multi-Bayesian control chart is explained. Finally, for instance, a multiple quality control process of the automatic transmission of the automobile is used to verify the performance evaluation and optimization of the multivariate FT VSI Bayesian control chart. The results show that the method has a better application.     

Monitoring change point for diffusion parameter based on discretely observed sample from stochastic differential equation models

Stochastic differential equation (SDE) models are useful in describing complex dynamical systems in science and engineering. In this study, we consider a monitoring procedure for an early detection of dispersion parameter change in SDE models. The proposed scheme provides a useful diagnostic analysis for phase I retrospective study and develops a flexible and effective control chart for phase II prospective monitoring. A standardized control chart is constructed, and a bootstrap method is used to estimate the mean and variance of the monitoring statistic. The control limit is obtained as an upper percentile of the maximum value of a standard Wiener process. The proposed procedure appears to have a manageable computational complexity for online implementation and also to be effective in detecting changes. We also investigate the performance of the exponentially weighted mean squared control charts for the continuous SDE processes. A simulation method is used to study the empirical sizes and the average run length characteristics of the proposed scheme, which also demonstrates the effectiveness of our method. Finally, we provide an empirical example for illustration. Copyright © 2014 John Wiley & Sons, Ltd.     

自相关过程的质量控制图

常规控制图应用的基本假设是从过程得到的测量值彼此独立,但许多连续型的制造业生产过程(例如化学和制药)往往存在自相关,此时常规控制图容易虚发警报。基于数据的样本自相关函数,本文改进了常规控制图的控制界限,使之适用于自相关过程,并运用常规X-s控制图和本文修正的X控制图对一个实际案例进行了比较分析,结果表明本文修正的X控制图可正确地判断过程是否处于受控状态。