Exploring Variability in Sea Level at a Tide Gauge Station through Control Charts

Monitoring temporal changes in sea level is important in assessing coastal risk.Sea level anomalies at a tide gauge station,if kinematically conceived,include systematic variations such as trend,acceleration,periodic oscillations,and random disturbances.Among them,the non-stationary nature of the random sea level variations of known or unknown origin at coastal regions has been long recognized by the sea level community.This study proposes the analyses of subgroups of random residual statistics of a rigorously formulated kinematic model solution of tide gauge variations using X-bar and S control charts.The approach is demonstrated using Key West,Florida tide gauge records.The mean and standard errors of 5-year-long subgroups of the residuals revealed that sea level changes at this location have been progressively intensifying from 1913 to the present.Increasing oscillations in sea level at this locality may be attributed partly to the thermal expansion of seawater with increasing temperatures causing larger buoyancy-related sea level fluctuations as well as the intensification of atmospheric events including wind patterns and the impact of changes in inverted barometer effects that will alter coastal risk assessments for the future.

Automated Identification of Basic Control Charts Patterns Using Neural Networks

The identification of control chart patterns is very important in statistical process control. Control chart patterns are categorized as natural and unnatural. The presence of unnatural patterns means that a process is out of statistical control and there are assignable causes for process variation that should be investigated. This paper proposes an artificial neural network algorithm to identify the three basic control chart patterns;natural, shift, and trend. This identification is in addition to the traditional statistical detection of runs in data, since runs are one of the out of control situations. It is assumed that a process starts as a natural pattern and then may undergo only one out of control pattern at a time. The performance of the proposed algorithm was evaluated by measuring the probability of success in identifying the three basic patterns accurately, and comparing these results with previous research work. The comparison showed that the proposed algorithm realized better identification than others.

Construction of Control Charts for Monitoring Various Parameters Related to the Management of the COVID-19 Pandemic

To monitor the quality characteristics of a process, appropriate graphical and statistical tools must be used. These tools are capable of showing the evolution over time of the behavior of the quality characteristics (measurable or countable) and detecting situations that seem to present certain anomalies. The control chart is one of these tools widely used in quality management. In the process of managing the COVID-19 pandemic, this tool will make it possible to know at all times whether the parameters monitored such as the positivity rate, the recovery rate, and the mortality rate, are under control and to act accordingly. Monitoring cure and mortality rates will also show us the effectiveness of the treatments used.

The Principle of Mathematical Induction Applied to the Generalized Model for the Economic Design of X-Control Charts

Rahim and Banerjee [1] developed a general model for the optimal design of x-control charts. The model minimizes the expected cost per unit time. The heart of the model is a theorem that derives the expected total cost and the expected cycle length. In this paper an alternative simple proof for the theorem is provided based on mathematical induction.

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.

Economic Design of & S Control Charts Based on Taguchi's Loss Function and Its Optimization

Much research effort has been devoted to economic design of X ＆ S control charts,however,there are some problems in usual methods.On the one hand,it is difficult to estimate the relationship between costs and other model parameters,so the economic design method is often not effective in producing charts that can quickly detect small shifts before substantial losses occur;on the other hand,in many cases,only one type of process shift or only one pair of process shifts are taken into consideration,which may not correctly reflect the actual process conditions.To improve the behavior of economic design of control chart,a cost ＆ loss model with Taguchi＇s loss function for the economic design of X ＆ S control charts is embellished,which is regarded as an optimization problem with multiple statistical constraints.The optimization design is also carried out based on a number of combinations of process shifts collected from the field operation of the conventional control charts,thus more hidden information about the shift combinations is mined and employed to the optimization design of control charts.At the same time,an improved particle swarm optimization（IPSO） is developed to solve such an optimization problem in design of X ＆ S control charts,IPSO is first tested for several benchmark problems from the literature and evaluated with standard performance metrics.Experimental results show that the proposed algorithm has significant advantages on obtaining the optimal design parameters of the charts.The proposed method can substantially reduce the total cost（or loss） of the control charts,and it will be a promising tool for economic design of 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.

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.

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.

Enhancing Software Process Management through Control Charts

In software development life cycle, Software Process Management (SPM) acts as a significant part throughout the execution of project. In this study, the application of control chart for analyzing the stability of software process and defects in the software product is discussed. This paper will discuss the analyzing impact or collision of rework effort, defect density, inspection performance and productivity by using control charts. This paper also explains the benefits and challenges of using control charts in software organization.

Monitoring Saccharification Process in Brewery Industry Using Quality Control Charts

The aim of this study was to establish a control system for saccharification process using quality control charts. To achieve this goal, temperature, pH and brix were measured at 12 minutes intervals for 15 consecutive batches which took 2 hours each. The time variations for three process parameters were assessed to establish a good understanding of the saccharification process. The temperature varied between 58℃ and 62℃ while the pH decreased slowly due to oxidation, values of which varied between 5.7 and 5.0. Brix values increased linearly with time. The initial and final values of the three parameters varied from one batch to another. Of the three parameters, brix was not well represented on the quality control charts due to wide difference between initial and final values during saccharification. The final brix values varied between batches, from 10.6% to 11.6%. The control charts used in this study were X-bar and Range charts. The rules for interpreting control charts were implemented for both X-bar and R charts, results of which showed that the process was out of control, although some rules were not violated due to little number of batches studied. The values of for temperature and pH data (2.27℃ and 0.35, respectively) were lower compared to brix data (11.2%). The corresponding values of span between control limits, SPx and SPR for temperature and pH were also comparatively lower than those established from brix data. Due to larger values of for brix measurements, the corresponding control charts for brix were insensitive in identifying out-of-control points during saccharification process.

Some Group Runs Based Multivariate Control Charts for Monitoring the Process Mean Vector

In this article, we propose two control charts namely, the “Multivariate Group Runs’ (MV-GR-M)” and the “Multivariate Modified Group Runs’ (MV-MGR-M)” control charts, based on the multivariate normal processes, for monitoring the process mean vector. Methods to obtain the design parameters and operations of these control charts are discussed. Performances of the proposed charts are compared with some existing control charts. It is verified that, the proposed charts give a significant reduction in the out-of-control “Average Time to Signal” (ATS) in the zero state, as well in the steady state compared to the Hotelling’s T2 and the synthetic T2 control charts.

基于Shewhart Control Chart的生鲜乳中兽药残留风险预警方法研究

针对生鲜乳中兽药残留水平动态变化的特点,本研究探索构建一种基于历史数据的生鲜乳中兽药残留动态预警方法。基于Shewhart Control Chart理论,建立了兽药残留超标预警、检出率异常预警和平均值标准偏差预警方法。对中国某大型乳企的生鲜乳中氟甲喹和达氟沙星检测数据分析发现,无需触发风险预警,同时对假定出现的检出率异常和平均值异常预警情况进行了分析。

即刻法和Levey-Jennings法在ELISA检测HBsAg中的比较

目的将2013年8月至2014年4月底每次ELISA法检测HBs Ag试验的前20次质量控制数据分别用即刻法和LeveyJennings法分析,探究这两种方法的优缺点及适用情况。方法对半年的质控数据先用即刻法统计分析,计算得到每组数据的x,CV,s,SI上限及SI下限,并将得到的SI上限,SI下限与SI界值表比较,若SI上限,SI下限均小于n2s,则表明试验在控,若有一值处于n2s和n3s之间,则为告警,若有一值大于n3s,则处于失控,对于失控和告警的数据都需舍去离散程度最大值,并查找原因,重新进行测定。同时对同批号质控物和同试剂的前20次质控数据进行计算得到,s,并以x,x±3s建立质控框架图,将随后数据绘入Levey-Jennings质控图中,大于x+3s或小于x-3s的质控值视为失控状态,需查找原因,重新测量。结果发现有两组数据在即刻法和Levey-Jennings法中呈现出不同的结果。即刻法中告警的数据在Levey-Jennings法中可以处于在控状态,而Levey-Jennings法失控的数据在即刻法中可能在控。结论即刻法和Levey-Jennings法适用不同条件下的检测,对于检测频率较低的样本,即刻法显得更为合适。对于HBs Ag来看,Levey-Jennings法更合适适用。

DevExpress图表控件XtraCharts在监控软件中的应用

使用XtraChart组件可以快捷地开发出相对专业的二维图表或三维图表软件。本文中通过一个监控软件的实例,介绍了该控件在WinForm上的使用和步骤。该实例实现了在一个图表中显示多种数据,每种数据和指定的坐标轴绑定,这个图表同时也能够动态更新和自动滚屏。

Calculation of One-Valued Control Limits by Control Chart of Angles

The data we use to express angle or direction are entitled directional data. In a plan right angled coordinate system the traditional control chart can’t solve the quality control problem which the characteristic value is angle. This paper analyses and calculates the one valued control limits by control chart of angles.

基于Levey-Jennings质控图联合Westgard多规则理论建立万古霉素治疗药物监测的室内质控评估方法

目的:利用Levey-Jennings质控图联合Westgard多规则理论建立高效液相色谱法测定万古霉素血药浓度的室内质控方法,为万古霉素安全有效的个体化给药提供依据。方法:取万古霉素标准品,溶解后加入空白血清制得质量浓度分别为10、25和50μg/mL的质控血浆,进行方法学考察以评估其可行性;对2020年6—8月该院30份万古霉素质控品进行监测,绘制Levey-Jennings质控图及Z-分数质控图,结合Westgard多规则理论对室内质控进行评估并进行统计分析。结果:万古霉素血清质量浓度在2.5~100μg/mL线性良好,低、中、高浓度质控品的日内和日间精密度的RSD及回收率均符合《中华人民共和国药典:四部》(2020年版)中生物样品测定的要求;室内质控评价结果显示万古霉素失控1次,经分析,去除误差因素后未有失控出现。结论:万古霉素治疗药物监测室内质量控制体系的建立有助于提高血药浓度监测结果的准确性,为临床提供精准的个体化药学服务。

HIV检测中建立Levey-Jennings质控图与"即刻法"质控的应用比较

[目的]比较Levey-Jennings质控图与"即刻法"质控的应用特点,为满足不同条件的实验提供选择。[方法]对外部质控血清连续检测20次,用其结果分别绘制质控图和进行"即刻法"质控统计。[结果]质控图使用累计和技术或趋势分析技术图形可提供系统误差的状况。"即刻法"质控经统计计算并与SI值表比较,能快速进入质控状态。[结论]质控图具有较高的检出分析误差能力,而对于检测频次较低的基层HIV初筛实验室"即刻法"质控更具有实际应用价值。

Westgard多规则控制方法结合Levey-Jennings质控图在TEG日常室内质控中的应用

目的通过应用Westgard多规则控制方法结合Levey-Jennings质控图对TEG分析仪进行日常室内质量控制与分析,持续改进检验质量,提高实验室TEG检测的精密度。方法应用Westgard多规则控制方法、Levey-Jennings质控图及同一批号质控品每日对TEG测定参数R值、K值、Angel值、MA值连续12个月进行室内质控监测分析,分别计算均值(x)、标准差(SD)和变异系数(CV%)来观察检验控制效果。结果应用此质量控制方法来及时纠正、分析和改善TEG室内质量控制中的系统错误,R值、K值、Angle值、MA值平均CV%值2019年1~6月为20.33%、13%、3.6%、9.65%;7~12月则分别减低为9%、3%、1.28%、5.35%。结论 Westgard多规则控制方法及Levey-Jennings质控图用于TEG室内质控检测结果可提升TEG临床检测结果的精密度。

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.