共查询到20条相似文献，搜索用时 15 毫秒
1.
Ross Sparks 《Quality and Reliability Engineering International》2015,31(8):1743-1760
The scan statistic is a popular choice for monitoring and detecting spatio‐temporal outbreaks. It can be designed to be optimal if the outbreak characteristics (shape and size) are known in advance. However, in all practical situations, neither the shape nor the size are known in advance. Therefore, there is a need for spatio‐temporal surveillance plans that perform well for a range of unknown outbreaks. This paper proposes a new approach for detecting spatio‐temporal outbreaks based on the cumulative sum of order statistics. The approach performed on average better than the simple scan statistic for both a range of outbreaks involving a single geographical region. More importantly, it performed significantly better than the simple scan plan for outbreaks involving simultaneous multiple (non‐overlapping) geographically dispersed regions. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Adaptive cumulative sum (ACUSUM) charts, which adjust the reference value dynamically based on estimated shift size, provide good performance in detecting a range of mean shifts. However, when the range is wide, ACUSUM may not perform well for small shifts over the range. An adaptive runs rule, which is motivated by the concept of supplementary runs rule, is proposed, in order to make control charts more sensitive to small mean shifts. The adaptive runs rule assigns scores to consecutive runs based on the estimated shift size of the mean. The ACUSUM chart is supplemented with the adaptive runs rule to enhance its sensitivity in detecting small mean shifts. The average run length performance of the ACUSUM chart with the adaptive runs rule is compared with those of cumulative sum and variants of adaptive charts including ACUSUM. The experimental results reveal that the ACUSUM chart with the adaptive runs rule achieves superior detection performance over a wide range of mean shifts. 相似文献
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The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution. It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement. The current study introduces control charts that help the manufacturing concerns to keep the production process in control. It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance. The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts. The findings suggest that an extended exponentially weighted moving average control chart based on the percentiles estimator performs better than exponentially weighted moving average control charts based on the percentiles estimator and modified maximum likelihood estimator. Further, these results will help the firms in the early detection of errors that enhance the process reliability of the telecommunications and financing industry. 相似文献
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Abdul Haq 《Quality and Reliability Engineering International》2013,29(7):1015-1025
Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are commonly used for monitoring the process mean. In this paper, a new hybrid EWMA (HEWMA) control chart is proposed by mixing two EWMA control charts. An interesting feature of the proposed control chart is that the traditional Shewhart and EWMA control charts are its special cases. Average run lengths are used to evaluate the performances of each of the control charts. It is worth mentioning that the proposed HEWMA control chart detects smaller shifts substantially quicker than the classical CUSUM, classical EWMA and mixed EWMA–CUSUM control charts. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Nasir Abbas Muhammad Riaz Ronald J. M. M. Does 《Quality and Reliability Engineering International》2013,29(5):653-663
Control charts are the most extensively used technique to detect the presence of special cause variations in processes. They can be classified into memory and memoryless control charts. Cumulative sum and exponentially weighted moving average control charts are memory‐type control charts as their control structures are developed in such a way that the past information is not ignored as it is done in the case of memoryless control charts, like the Shewhart‐type control charts. The present study is based on the proposal of a new memory‐type control chart for process dispersion. This chart is named as CS‐EWMA chart as its plotting statistic is based on a cumulative sum of the exponentially weighted moving averages. Comparisons with other memory charts used to monitor the process dispersion are done by means of the average run length. An illustration of the proposed technique is done by applying the CS‐EWMA chart on a simulated dataset. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Babar Zaman Muhammad Riaz Nasir Abbas Ronald J.M.M. Does 《Quality and Reliability Engineering International》2015,31(8):1407-1421
Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM) charts are famous statistical tools, to handle special causes and to bring the process back in statistical control. Shewhart charts are useful to detect large shifts, whereas EWMA and CUSUM are more sensitive for small to moderate shifts. In this study, we propose a new control chart, named mixed CUSUM‐EWMA chart, which is used to monitor the location of a process. The performance of the proposed mixed CUSUM‐EWMA control chart is measured through the average run length, extra quadratic loss, relative average run length, and a performance comparison index study. Comparisons are made with some existing charts from the literature. An example with real data is also given for practical considerations. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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Seyed Soheil Hosseini Rassoul Noorossana 《Quality and Reliability Engineering International》2018,34(4):477-500
Detection of communication outbreak among members of a network or a subgroup of a network has been a topic of interest in the literature of social network analysis. One approach to monitoring changes in a social network is to monitor graph measures related to the network representation in each period and detecting anomalies by applying a control chart. In this paper, we compare the performance of average degree and standard deviation of degree measures of a network for detecting outbreaks on a weighted undirected network using exponentially weighted moving average and cumulative sum control charts. Evaluation results indicate that average degree measure is better in detecting small changes than standard deviation of degree measure. Whereas for greater changes and outbreaks consisting of more members of the network, the opposite is true. In addition, exponentially weighted moving average control charts perform better than cumulative sum in detecting smaller changes and outbreaks consisting of less members of the network. 相似文献
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Nasir Abbas Muhammad Riaz Ronald J. M. M. Does 《Quality and Reliability Engineering International》2013,29(3):345-356
The control chart is a very popular tool of statistical process control. It is used to determine the existence of special cause variation to remove it so that the process may be brought in statistical control. Shewhart‐type control charts are sensitive for large disturbances in the process, whereas cumulative sum (CUSUM)–type and exponentially weighted moving average (EWMA)–type control charts are intended to spot small and moderate disturbances. In this article, we proposed a mixed EWMA–CUSUM control chart for detecting a shift in the process mean and evaluated its average run lengths. Comparisons of the proposed control chart were made with some representative control charts including the classical CUSUM, classical EWMA, fast initial response CUSUM, fast initial response EWMA, adaptive CUSUM with EWMA‐based shift estimator, weighted CUSUM and runs rules–based CUSUM and EWMA. The comparisons revealed that mixing the two charts makes the proposed scheme even more sensitive to the small shifts in the process mean than the other schemes designed for detecting small shifts. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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The cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts have been widely accepted because of their fantastic speed in identifying small‐to‐moderate unusual variations in the process parameter(s). Recently, a new CUSUM chart has been proposed that uses the EWMA statistic, called the CS‐EWMA chart, for monitoring the process variability. On similar lines, in order to further improve the detection ability of the CS‐EWMA chart, we propose a CUSUM chart using the generally weighted moving average (GWMA) statistic, named the GWMA‐CUSUM chart, for monitoring the process dispersion. Monte Carlo simulations are used to compute the run length profiles of the GWMA‐CUSUM chart. On the basis of the run length comparisons, it turns out that the GWMA‐CUSUM chart outperforms the CUSUM and CS‐EWMA charts when identifying small variations in the process variability. A simulated dataset is also used to explain the working and implementation of the CS‐EWMA and GWMA‐CUSUM charts. 相似文献
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Jyun‐You Chiang Tzong‐Ru Tsai Nan‐Cheng Su 《Quality and Reliability Engineering International》2018,34(4):589-608
The standard Shewhart‐type chart, named FSS‐ chart, has been widely used to detect the mean shift of process by implementing fixed sample and sampling frequency schemes. The FSS‐ chart could be sensitive to the normality assumption and is inefficient to catch small or moderate shifts in the process mean. To monitor nonnormally distributed variables, Li et al [Commun Stat‐Theory Meth. 2014; 43(23):4908‐4924] extended the study of Tsai [Int J Reliab Qual Saf Eng. 2007; 14(1):49‐63] to provide a new skew‐normal FSS‐ (SN FSS‐ ) chart with exact control limits for the SN distribution. To enhance the sensitivity of the SN FSS‐ chart on detecting small or moderate mean shifts in the process, adaptive charts with variable sampling interval (VSI), variable sample size (VSS), and variable sample size and sampling interval (VSSI) are introduced for the SN distribution in this study. The proposed adaptive control charts include the normality adaptive charts as special cases. Simulation results show that all the proposed SN VSI‐ , SN VSS‐ , and SN VSSI‐ charts outperform the SN FSS‐ chart on detecting small or moderate shifts in the process mean. The impact of model misspecification on using the proposed adaptive charts and the sample size impact for using the FSS‐ chart to monitor the mean of SN data are also discussed. An example about single hue value in polarizer manufacturing process is used to illustrate the applications of the proposed adaptive charts. 相似文献
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Abdul Haq Jennifer Brown Elena Moltchanova 《Quality and Reliability Engineering International》2014,30(5):697-710
Exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts have found extensive applications in industry. The sensitivity of these quality control schemes can be increased by using fast initial response (FIR) features. In this paper, we introduce some improved FIR features for EWMA and CUSUM control charts and evaluate their performance in terms of average run length. We compare the proposed FIR‐based EWMA and CUSUM control schemes with some existing control schemes, that is, EWMA, FIR‐EWMA, CUSUM, and FIR‐CUSUM. It is noteworthy that the proposed control schemes are uniformly better than the other schemes considered here. An illustrative example is also given to demonstrate the implementation of the proposed control schemes. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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张有正 《中国计量学院学报》2004,15(2):131-133
{N(t),t>0}是一强度为λt的Poisson过程,Xk,Tk,k≥1为第k个单位的规模大小及进入系统的时刻,讨论了若单元进入系统后规模随时间而变化的情况下,得到了一类加权随机和,并给出了其几乎处处收敛性. 相似文献
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Vasileios Alevizakos Kashinath Chatterjee Christos Koukouvinos 《Quality and Reliability Engineering International》2021,37(4):1504-1523
Nonparametric control charts are used in process monitoring when there is insufficient information about the form of the underlying distribution. In this article, we propose a triple exponentially weighted moving average (TEWMA) control chart based on the sign statistic for monitoring the location parameter of an unknown continuous distribution. The run-length characteristics of the proposed chart are evaluated performing Monte Carlo simulations. We also compare its statistical performance with existing nonparametric sign charts, such as the cumulative sum (CUSUM), exponentially weighted moving average (EWMA), generally weighted moving average (GWMA), and double exponentially weighted moving average (DEWMA) sign charts as well as the parametric TEWMA-
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Ahmad Ostadsharif Memar Seyed Taghi Akhavan Niaki 《Quality and Reliability Engineering International》2011,27(4):499-514
A traditional approach to monitor both the location and the scale parameters of a quality characteristic is to use two separate control charts. These schemes have some difficulties in concurrent tracking and interpretation. To overcome these difficulties, some researchers have proposed schemes consisting of only one chart. However, none of these schemes is designed to work with individual observations. In this research, an exponentially weighted moving average (EWMA)‐based control chart that plots only one statistic at a time is proposed to simultaneously monitor the mean and variability with individual observations. The performance of the proposed scheme is compared with one of the two other existing combination charts by simulation. The results show that in general the proposed chart has a significantly better performance than the other combination charts. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
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Vasileios Alevizakos Kashinath Chatterjee Christos Koukouvinos 《Quality and Reliability Engineering International》2021,37(6):2622-2645
Nonparametric (or distribution-free) control charts are used for monitoring processes where there is a lack of knowledge about the underlying distribution. In this article, a triple exponentially weighted moving average control chart based on the signed-rank statistic (referred as TEWMA-SR chart) is proposed for monitoring shifts in the location parameter of an unknown, but continuous and symmetric, distribution. The run-length characteristics of the proposed chart are evaluated performing Monte Carlo simulations. A comparison study with other existing nonparametric control charts based on the signed-rank statistic, the TEWMA sign chart, and the parametric TEWMA-
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Michael B. C. Khoo 《Quality and Reliability Engineering International》2004,20(6):617-635
The p chart is often used to monitor the fraction of non‐conforming products. However, the p chart is slow in detecting sustaining shifts of small magnitude in the level of fraction non‐conforming. This paper discusses a more efficient alternative to the standard p chart approach, i.e. the construction of a moving average control chart for fraction non‐conforming, p. Approximations by means of mathematical calculations and the corresponding simulation results for the average run length profiles show that the performance of the new approach is superior to that of the standard approach. The new approach is easy to implement and hence might be attractive and useful to practitioners. Examples are also given to show how the proposed procedure is put to work in real situations. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
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Ronald J.M.M. Does Rob Goedhart William H. Woodall 《Quality and Reliability Engineering International》2020,36(8):2610-2620
When designing control charts the in-control parameters are unknown, so the control limits have to be estimated using a Phase I reference sample. To evaluate the in-control performance of control charts in the monitoring phase (Phase II), two performance indicators are most commonly used: the average run length (ARL) or the false alarm rate (FAR). However, these quantities will vary across practitioners due to the use of different reference samples in Phase I. This variation is small only for very large amounts of Phase I data, even when the actual distribution of the data is known. In practice, we do not know the distribution of the data, and it has to be estimated, along with its parameters. This means that we have to deal with model error when parametric models are used and stochastic error because we have to estimate the parameters. With these issues in mind, choices have to be made in order to control the performance of control charts. In this paper, we discuss some results with respect to the in-control guaranteed conditional performance of control charts with estimated parameters for parametric and nonparametric methods. We focus on Shewhart, exponentially weighted moving average (EWMA), and cumulative sum (CUSUM) control charts for monitoring the mean when parameters are estimated. 相似文献
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Nong Ye Connie Borror Yebin Zhang 《Quality and Reliability Engineering International》2002,18(6):443-451
Intrusion detection is used to monitor and capture intrusions into computer and network systems, which attempt to compromise the security of computer and network systems. To protect information systems from intrusions and thus assure the reliability and quality of service of information systems, it is highly desirable to develop techniques that detect intrusions into information systems. Many intrusions manifest in dramatic changes in the intensity of events occurring in information systems. Because of the ability of exponentially weighted moving average (EWMA) control charts to monitor the rate of occurrences of events based on the their intensity, we apply three EWMA statistics to detect anomalous changes in the events intensity for intrusion detections. They include the EWMA chart for autocorrelated data, the EWMA chart for uncorrelated data and the EWMA chart for monitoring the process standard deviation. The objectives of this paper are to provide design procedures for realizing these control charts and investigate their performance using different parameter settings based on one large dataset. The early detection capability of these EWMA techniques is also examined to provide the guidance about the design capacity of information systems. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献