Memory-Type Control Charts Through the Lens of Cost Parameters

A memory-type control chart utilizes previous information for chart construction.An example of a memory-type chart is an exponentially-weighted moving average(EWMA)control chart.The EWMA control chart is well-known and widely employed by practitioners for monitoring small and moderate process mean shifts.Meanwhile,the EWMA median chart is robust against outliers.In light of this,the economic model of the EWMA and EWMA median control charts are commonly considered.This study aims to investigate the effect of cost parameters on the out-of-control average run lengthðARL_(1)Þin implementing EWMA and EWMA median control charts.The economic model was used to compute the ARL_(1) parameter.The 14 input parameters were identified and the analysis was carried out based on the one-parameter-at-a-time basis.When the input parameters change based on a predetermined percentage,the ARL_(1) is affected.According to the results of the EWMA chart,nine input parameters had an effect andfive input parameters had no effect on the ARL_(1) parameter.Further,only seven of the 14 input parameters had an effect on the ARL_(1) of the EWMA median chart.However,the effect of each input parameter on the ARL_(1) was different.Moreover,the ARL_(1) for the EWMA median chart was smaller than the EWMA chart.This analysis is crucial to observe and determine the input parameters that have a significant impact on the ARL_(1) of the EMWA and EWMA median control charts.Hence,practitioners can obtain an overview of the influence of the input parameters on the ARL_(1) when implementing the EWMA and EWMA median control charts.

Computation of Average Run Length for Residual-Based T^2 Control Chart for Multivariate Autocorrelated Processes

The expression of residual is obtained according to its dynamic response to mean shift, then the distribu- tion of T2 statistic applied to the residual is derived, thus the probability of the 7a statistic lying outside the control limit is calculated. The above-mentioned results are substituted into the infinite definition expression of the average run length （ARL）, and then the final finite ARL expression is obtained. An example is used to demonstrate the procedures of the proposed method. In the comparative study, eight autocorrelated processes and four different mean shifts are performed, and the ARL values of the proposed method are compared with those obtained by simulation method with 50 000 replications. The accuracy of the proposed method can be illustrated through the comparative results.

Control charts for the Pareto distribution

The Pareto distribution plays an important role in various areas of research. In this paper, the average run length （ARL） unbiased control charts, which monitor the shape and threshold parameters of the Pareto distribution respectively, are proposed when the incontrol parameters are known. The effects of parameter estimation on the performance of the proposed control charts are also studied. Results show that the control charts with the estimated parameters are not suitable to be used in the known parameter case, thus the ARL-unbiased control charts for the shape and threshold parameters with the desired ARLo, which consider the variability of the parameter estimates, are further developed. The performance of the proposed control charts is investigated in terms of the ARL. Finally, an example is given to illustrate the proposed control charts.

Control Charts for the Shape Parameter of Power Function Distribution under Different Classical Estimators

In practice,the control charts for monitoring of process mean are based on the normality assumption.But the performance of the control charts is seriously affected if the process of quality characteristics departs from normality.For such situations,we have modified the already existing control charts such as Shewhart control chart,exponentially weighted moving average(EWMA)control chart and hybrid exponentially weighted moving average(HEWMA)control chart by assuming that the distribution of underlying process follows Power function distribution(PFD).By considering the situation that the parameters of PFD are unknown,we estimate them by using three classical estimation methods,i.e.,percentile estimator(P.E),maximum likelihood estimator(MLE)and modified maximum likelihood estimator(MMLE).We construct Shewhart,EWMA and HEWMA control charts based on P.E,MLE and MMLE.We have compared all these control charts using Monte Carlo simulation studies and concluded that HEWMA control chart under MLE is more sensitive to detect an early shift in the shape parameter when the distribution of the underlying process follows power function distribution.

The New Neutrosophic Double and Triple Exponentially Weighted Moving Average Control Charts

The concept of neutrosophic statistics is applied to propose two monitoring schemes which are an improvement of the neutrosophic exponentially weighted moving average(NEWMA)chart.In this study,two control charts are designed under the uncertain environment or neutrosophic statistical interval system,when all observations are undermined,imprecise or fuzzy.These are termed neutrosophic double and triple exponentially weighted moving average(NDEWMA and NTEWMA)control charts.For the proficiency of the proposed chart,Monte Carlo simulations are used to calculate the run-length characteristics(such as average run length(ARL),standard deviation of the run length(SDRL),percentiles(P_(25),P_(50),P_(75)))of the proposed charts.The structures of the proposed control charts are more effective in detecting small shifts while these are comparable with the other existing charts in detecting moderate and large shifts.The simulation study and real-life implementations of the proposed charts show that the proposed NDEWMA and NTEWMA charts perform better in monitoring the process of road traffic crashes and electric engineering data as compared to the existing control charts.Therefore,the proposed charts will be helpful in minimizing the road accident and minimizing the defective products.Furthermore,the proposed charts are more acceptable and actual to apply in uncertain environment.

Parameters optimization for exponentially weighted moving average control chart using generalized regression neural network

As a useful alternative of Shewhart control chart, exponentially weighted moving average （EWMA） control chat has been applied widely to quality control, process monitoring, forecast, etc. In this paper, a method was introduced for optimal design of EWMA and multivariate EWMA （MEWMA） control charts, in which the optimal parameter pair （ λ, k） or （ λ, h ） was searched by using the generalized regression neural network （GRNN）. The results indicate that the optimal parameter pair can be obtained effectively by the proposed strategy for a given in-control average running length （ARLo） and shift to detect under any conditions, removing the drawback of incompleteness existing in the tables that had been reported.

非参数自适应EWMA SR控制图及其变采样间隔设计

本文基于Wilcoxon符号秩(Signed Rank, SR)检验统计量,提出了一种非参数自适应指数加权移动平均(Adaptive Exponentially Weighted Moving Average, AEWMA)控制图。所提出的AEWMA SR控制图结合了非参数统计量的稳健受控性能以及自适应控制图良好的整体偏移检测特性。同时,为了提高固定采样间隔下的非参数AEWMA SR静态控制图对异常偏移的检测效率,本文进一步研究了可变采样间隔(Variable Sampling Intervals, VSI)下的非参数AEWMA SR动态控制图设计问题。使用了Markov链方法计算控制图的精确平均运行链长(Average Run Length, ARL)和平均报警时间(Average Time to Signal, ATS)等性能指标。通过仿真分析比较了VSI AEWMA SR控制图、FSI AEWMA SR控制图和VSI EWMA SR控制图的统计性能。结果表明,所提出的VSI AEWMA SR控制图能兼顾对于不同大小偏移的敏感性,且变采样间隔的动态策略能显著提高控制图的检测效率。

监控不合格品率的MEWMA-p控制图设计

传统Shewhart-p控制图只对单一属性的不合格品率进行监控,在过程发生偏移时有一定的滞后性。为提高不合格品率控制图的精度,提出一种多元指数加权移动平均不合格品率(multivariate exponentially weighted moving average p, MEWMA-p)控制图。该控制图将多个属性的不合格品率应用于多元指数加权移动平均控制图,可同时对多个属性进行监控,并且对于小范围的偏移更加敏感。对比分析同等偏移程度下指数加权移动平均不合格品率(exponentially weighted moving average p, EWMA-p)控制图与MEWMA-p控制图的平均运行长度(average run length,ARL)结果,并通过模拟仿真说明该方法的有效性。

通用型指数加权移动平均控制图的设计

为提高质量控制图监测微小到中等过程偏移的灵敏度,文章提出一种新的用于过程均值监控的通用型指数加权移动平均(UEWMA)控制图,该控制图是EWMA控制图的一般性推广,根据数据特征,自定义选取平滑系数λ_(1),λ_(2),…,λ_(s),使控制效果达到最优;给出UEWMA控制图的均值与控制限的求取方法,并推导出平均运行长度(ARL)和运行长度标准偏差(SDRL);最后,研究平滑系数对该控制图性能的影响,并将其与现有控制图监测微小到中等过程偏移的灵敏度进行比较。研究结果表明,UEWMA控制图通过数据特征设计平滑系数,具有灵活性好、灵敏度高、扩展性强和控制效果好的特点。

基于对抗自编码的风电齿轮箱异常状态识别

对风电机组进行早期异常状态识别,有助于提高机组可靠性、降低运维成本。文章基于监控与数据采集(SCADA)系统数据,提出了一种基于卷积对抗自编码器的风电齿轮箱异常状态识别模型。首先,用预处理后的健康SCADA数据训练卷积对抗自编码器,根据训练结果自适应确定异常状态阈值;然后,将所有数据输入到训练好的模型中,利用自编码器的输入和输出计算曼哈顿距离作为健康状态的度量,使用指数加权移动平均控制图显示结果。由于不同机组所处运行工况不同,每个机组单独训练并测试。现场风电齿轮箱故障案例验证了方法的有效性。

向量自回归和T^(2)控制图在变工况齿轮箱故障检测中的应用

针对齿轮箱传统故障分析方法难以评估变工况下齿轮箱健康状态,对齿轮箱的振动数据按工况分类后,进行了基于向量自回归模型(vector autoregression,VAR)和统计过程控制方法的变工况下齿轮箱异常检测方法研究。采用时域同步平均算法(time synchronous averaging,TSA)去除原始振动信号中的噪声,并分工况建立向量自回归模型计算残差;提取残差的均方根(root square mean,RMS)和整流平均值作为指标,初步判断齿轮故障;选取残差的均方根及整流平均值进行统计过程分析,建立多变量指数加权平均(multivariate exponential weighted moving average,MEWMA)、广义方差以及T2控制图来判断齿轮早期异常发生点。研究结果表明,均方根T2控制图效果最佳,检测出了60、151、152三个异常点,从而完成了对变工况下齿轮箱的故障检测。

一种大动态范围数字 AGC快速控制算法

在大动态范围的复杂通信系统中,自动增益控制系统的性能起着至关重要的作用。针对传统自动增益控制系统的动态范围较小及收敛速度较慢的问题,提出了一种大动态范围数字AGC快速控制算法。该算法采用射频峰值检测以及大信号指示的方式实现对射频功率的快速检测;采用平均功率的方式对中频信号功率进行滑动平均,准确获取中频信号的平均功率;结合中频和射频增益控制策略,对接收信道的增益进行分配以及快速控制,使得射频信号经过射频单元后始终位于模数转换器(Analog to Digital Converter,ADC)的动态范围内,从而实现射频信号的稳定接收。仿真结果表明,相较于传统算法,所提算法的收敛时间由毫秒级提高到了微秒级,动态范围大幅提升。

基于协变量信息的自适应MEWMA控制图

在统计过程控制中,质量变量通常会受到许多协变量因素的影响,充分利用协变量的有用信息可以进一步提高控制图的灵敏度,因此提出一种新的自适应多元EWMA控制图,并计算ARL进行比较。在MEWMA控制图的基础上引入一个权重函数,根据协变量的有用信息自适应的调节统计量的加权参数:当收集到的协变量信息发生偏移时,选择较大的加权参数,更关注当前和附近时间点观测值的偏移程度;反之则选择较小的参数。大量数值模拟分析表明,充分利用协变量中的有用信息之后,监控效果明显优于MEWMA、MCUSUM控制图。

A new auxiliary information based cumulative sum median control chart for location monitoring

Control charts are commonly used tools in statistical process control for the detection of shifts in process parameters. Shewhart-type charts are efficient for large shift values, whereas cumulative sum(CUSUM) charts are effective in detecting medium and small shifts. Control chart use commonly assumes that data are free of outliers and parameters are known or correctly estimated based on an in-control process. In practice, these assumptions are not often true because some processes occasionally have outliers. Monitoring the location parameter is usually based on mean charts, which are seriously affected by violations of these assumptions. In this paper we propose several CUSUM median control charts based on auxiliary variables, and offer comparisons with their corresponding mean control charts. To monitor the location parameter, we examined the performance of mean and median control charts in the presence and absence of outliers. Both symmetric and non-symmetric processes were studied to examine the properties of the proposed control charts to monitor the location parameter using CUSUM control charts. We used different run length measures to study in-control and out-of-control performances of CUSUM charts. Results revealed that our proposed control charts perform much better than the traditional charts in the presence of outliers. A real application of our study was provided using data on concrete compressive strength as it relates to the quality of cement manufacturing.

基于预防维修的可变抽样区间泊松EWMA控制图经济设计

现代质量控制的核心技术和方法始终围绕着如何提高监控效率和降低控制成本问题而展开。统计过程控制是一种常用的质量控制方法,其重要的工具——控制图对过程中的质量特性值进行统计并描点达到监控过程质量状态的目的。控制图的设计方法将会对产品过程的监控效率和控制成本产生较大影响。针对只考虑传统控制图参数固定以及控制图统计设计的情形,传统的缺陷数c控制图基于泊松分布建立以监控制造过程中产品的缺陷数。为了降低控制过程成本并提高缺陷数c控制图的监控效率,研究预防维修策略下可变抽样区间(VSI) EWMA图的经济设计问题。首先,建立泊松分布下VSI EWMA控制图的经济模型。其次,令单位时间的损失成本函数最小得到经济模型的最优解。以化工建材行业为例,说明如何根据预防维修策略下所构建的控制图经济模型得到最优参数。然后,为得到设计参数与模型参数的影响关系,对经济模型灵敏度分析。最后,对经济模型进行最优性分析验证其优越性。

基于概率SVDD的控制图研究

基于支持向量数据描述算法,构建一种有效的指数加权移动平均控制图,用于监控高维数据的生产情况。通过模拟仿真,对所提出的控制图及原有控制图的性能进行研究分析。模拟结果表明,基于概率支持向量数据描述算法的指数加权移动平均控制图在检测小偏移方面比原有控制图更有效。

基于动态、非正态EWMA控制图的废旧产品再制造质量控制方法

鉴于废旧件的原始质量与服役工况不确定,导致其再制造过程波动性大、加工时段不连续等问题,提出一种基于动态、非正态分布指数加权移动平均控制图的再制造过程质量控制方法。根据非参数方法中的Wilcoxon秩和检验的理论知识,应用秩统计量,获得与样本数据分布无关的统计量;在此基础上,通过不断移动控制图数据窗口来更新在线观测点,并利用得分函数获得动态的光滑参数,构建面向动态、非正态分布的再制造过程质量EWMA控制图,实现了动态再制造过程质量的自适应监控。以废旧TPX6113镗床的导轨再制造过程为例,对其再制造过程质量进行动态监控,结果表明,所提方法能够快速监控到质量异常,且相比于其他控制图具有更好的监控性能,证明了该方法的有效性和可行性,为再制造过程实际的质量监控提供了一种有效的途径。

移动差值控制图评估临床实验室肌钙蛋白不确定度

目的运用控制图评估肌钙蛋白I(cTnI)测量不确定度。方法采用日本东曹AIA-1800全自动荧光磁微粒酶免分析仪测定cTnI控制品,1次/天,共30d;用Anderson-Darling法检验数据的正态分布性和独立性;建立单值-移动差值及指数加权移动平均值控制图及评估不确定度。结果 Anderson-Darling检验cTnI质控数据为正态分布性且具有独立性,结果测量不确定为(0.218±0.016)μg/L,(k=2)。结论移动极差控制图法可用来评估cTnI结果不确定度,本研究为临床实验室评价不确定度提供了新的思路。

自相关过程协方差阵的残差MEWMA控制图

本文研究多变量自相关过程协方差矩阵的质量监控问题.针对服从VAR(1)模型的多变量自相关过程,基于残差分析思想,将多变量指数加权移动平均(MEWMA)控制图用于对过程的监控.首先对残差MEWMA控制图统计量进行了推导,其次采用MonteCarlo仿真的方法,以平均运行链长为评价准则对残差MEWMA控制图的监控效果进行了分析.仿真结果表明,残差MEWMA控制图具有较好的监控效果.

统计质量保证技术在分析测试实验室内部质量控制中的应用

对通过统计质量保证 (SQA)技术进行分析测试实验室内部质量控制 (IQC)的方法作了初探。研究结果表明 ,SQA技术的应用能保证实验室始终处于统计受控状态 ,确保测试数据的有效性 ,有利于分析测试实验室质量保证活动的开展。