共查询到20条相似文献，搜索用时 15 毫秒
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Zaka et al provided a new distribution called the Weighted Power function distribution (WPFD), which has application in reliability engineering and survival analysis. They used different estimation methods to estimate the unknown parameters of WPFD and proved that modified maximum likelihood estimator (MMLE) is best to consider for the estimation of parameters. We have constructed the memoryless and memory-based control charts based on the assumption that the distribution of the underlying process does not follow the normal distribution. In this paper, we provide modified control charts using MMLE of the shape parameter for WPFD. We develop control charts to keep the process in control when the distribution of errors of underlying process follows WPFD. We propose the modified memoryless control chart, that is, Shewhart control chart and modified memory-based control chart, that is, Exponentially weighted moving average (EWMA) and Hybrid exponentially weighted moving average (HEWMA) control charts. We have made the comparison of the proposed control charts using Monte Carlo simulation and the real-life application for both and the memoryless control charts and memory-based control charts. We see that HEWMA based on MMLE performs better as compared to other proposed control charts. 相似文献
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Azam Zaka Ahmad Saeed Akhter Riffat Jabeen Aamir Sanaullah 《Quality and Reliability Engineering International》2021,37(6):2458-2477
The reflected power function distribution (RPFD) has applications in the fields of reliability engineering and survival analysis. To identify and remove the variation in different reliability processes and also to monitor the reliability of machines where the number of errors follows RPFD, we develop control charts to keep the process in control. A memory less control chart like a Shewhart control chart, and two memory-based control charts like an exponentially weighted moving average (EWMA) control chart and a hybrid exponentially weighted moving average (HEWMA) control chart are discussed and compared with each other. Proposal of these control charts is based on two different estimators, the percentile estimator (PE) and the modified maximum likelihood estimator (MMLE). This study shows that an HEWMA control chart based on PE performs better than PE-based Shewhart and EWMA control charts, as well as MMLE-based Shewhart, EWMA, and HEWMA control charts. 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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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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Marcelo Bourguignon Linda Lee Ho Fidel Henrique Fernandes 《Quality and Reliability Engineering International》2020,36(4):1333-1363
In this paper, we propose control charts for monitoring the Birnbaum-Saunders (BS) median parameter (scale parameter) on the basis of three estimators. Comparison of the control charts in terms of average run length using probability control limits and those based on asymptotic distribution of three estimators for the median parameter is developed. We also present guidelines for practitioners about the minimum sample size needed to match out-of-control average run length with the asymptotic control limits in function of the median parameter after an extensive simulation study. Numerical example illustrates the applied monitoring of BS median parameter. 相似文献
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Salma Riaz Muhammad Riaz Amna Nazeer Zawar Hussain 《Quality and Reliability Engineering International》2017,33(8):2653-2665
The motivation for this study is to analyze Bayesian exponentially weighted moving average (EWMA) control chart under 3 loss functions namely, SELF, LLF, and PLF. Informative priors (normal and mixture of normal) and non‐informative priors (Uniform and Jefferys) are considered for the analysis. The performance of Bayesian EWMA control chart using posterior and posterior predictive distribution scheme has been evaluated using average run length (ARL) and standard deviation run length (SDRL) as performance measures. Monte Carlo simulations are used to compute the performance measures for different values of smoothing constant. An illustrative example is also presented for practical considerations of Bayesian EWMA control chart. 相似文献
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Monitoring changes in the Weibull mean and variance simultaneously is of interest in quality control. The mean and variance of a Weibull process are determined by its shape and scale parameters. Most studies are focused on monitoring the Weibull scale parameter with fixed shape parameter or the Weibull shape parameter with fixed scale parameter. In this paper, we propose an exponentially weighted moving average chart based on the likelihood‐ratio test and an inverse error function called ELR chart to monitor changes in the Weibull mean and variance simultaneously. The simulation approach is used to derive the average run length. We compare our proposed chart with other existing control charts for 3 cases, including scale parameter changes with fixed shape parameter, shape parameter changes with fixed scale parameter, and both parameters changes. The results show that the ELR chart outperforms the other control charts in terms of average run length in most cases. Two numerical examples are used to illustrate the applications of the proposed control chart. 相似文献
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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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The Generally Weighted Moving Average Control Chart for Detecting Small Shifts in the Process Mean 总被引：2，自引：0，他引：2
A generalization of the exponentially weighted moving average (EWMA) control chart is proposed and analyzed. The generalized control chart we have proposed is called the generally weighted moving average (GWMA) control chart. The GWMA control chart, with time-varying control limits to detect start-up shifts more sensitively, performs better in detecting small shifts of the process mean. We use simulation to evaluate the average run length (ARL) properties of the EWMA control chart and GWMA control chart. An extensive comparison reveals that the GWMA control chart is more sensitive than the EWMA control chart for detecting small shifts in the mean of a process. To enhance the detection ability of the GWMA control chart, we submit the composite Shewhart-GWMA scheme to monitor process mean. The composite Shewhart-GWMA control chart with/without runs rules is more sensitive than the GWMA control chart in detecting small shifts of the process mean. The resulting ARLs obtained by the GWMA control chart when the assumption of normality is violated are discussed. 相似文献
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Murat C. Testik George C. Runger Connie M. Borror 《Quality and Reliability Engineering International》2003,19(1):31-38
In this paper, the robustness of the multivariate exponentially weighted moving average (MEWMA) control chart to non‐normal data is examined. Two non‐normal distributions of interest are the multivariate distribution and the multivariate gamma distribution. Recommendations for constructing MEWMA control charts when the normality assumption may be violated are provided. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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Waqas Arshad Nasir Abbas Muhammad Riaz Zawar Hussain 《Quality and Reliability Engineering International》2017,33(2):323-336
Quality has become a key determinant of success in all aspects of industry. Exponentially weighted moving average control chart is an important tool of statistical process control used to monitor and improve quality of industrial processes. To enhance the performance of control charts, there are many strategies including the choice of an efficient plotting statistic, the choice of an efficient sampling design, the application of runs rules, and the use auxiliary information among many others. In this study, we propose nine different signaling schemes to enhance the performance of an exponentially weighted moving average control chart for location parameter, which is based on the exploitation of auxiliary information. Performance evaluation of the proposed schemes is carried out in terms of average run length. Comparisons of proposals are made with the classical as well as the auxiliary based exponentially weighted moving average and cumulative sum charts, which indicate that the proposed schemes perform better than the comparative counterparts under discussion. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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We study a widely recommended acceptance sampling approach based on the use of an exponentially weighted moving average statistic. A correct mathematical assessment of the resulting sampling plans shows that the required statistical performance cannot be maintained over time. For this reason, these plans are flawed and thus should not be used. 相似文献
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Xin Lai Xiao Li Liu Liu Jiayin Wang Xuanping Zhang Xiaoyan Zhu Paul B. S. Lai 《Quality and Reliability Engineering International》2024,40(2):1042-1060
Risk-adjusted control charts have been widely used in monitoring surgical quality in detecting risks of surgical performance. Most of the previous approaches focus on shifts in the location parameter as well as the existence of the scale parameter, which cannot get the full measure of the scale parameter under different levels. Ignoring the magnitude of the scale parameter, the monitoring methods cannot detect different variations of surgical mortality that is measured by scale parameter and required to reflect surgical quality improvement. The method of detecting variations in surgical quality is of interest in surgical quality improvement. This paper uses a new weighted h-likelihood method to obtain a weighted score test for the surgical risks from the logistic model. Then an exponentially weighted moving average chart can be constructed to monitor the changes in the variance of risks, which could be of interest in practical surgical monitoring programs. Simulation results indicate that the proposed approach performs more efficiently than existing methods under various magnitudes of shifts in scale parameters on top of different pre-set threshold stability. In addition, the application of the proposed method to real surgical data from the Surgical Outcome Monitoring and Improvement Program in Hong Kong shows the improvement and deterioration in a hospital's outcomes. 相似文献
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Ross Sparks 《Quality and Reliability Engineering International》2016,32(5):1871-1888
This paper investigates detecting significant increases in communication patterns and levels between small groups of individuals within a moderate‐size targeted group. Potential applications range from trying to establish emerging thought leaders within an organisation to the detection of the planning stages of a crime. The scan statistic is a popular choice for monitoring and detecting spatio‐temporal outbreaks, but it is difficult to apply to large‐scale target groups because of the computational effort required. When monitoring communication levels between thousands of people, the number of combinations of people whose communication may have increased is very high, and to scan through all of these to find which combinations have increased communications significantly is an enormous task. A successful surveillance plan will have early communication outbreak detection properties and good diagnostic capabilities for identifying individuals contributing to this outbreak. This paper proposes a new computationally feasible approach for detecting communication outbreaks based on exponentially weighted moving average smoothed communication counts between individuals within the network. We apply a cumulative sum of ordered signal‐to‐noise (SN) ratios for communication counts to flag significant departures from their respective median values. This plan is demonstrated to be efficient at detecting changes in communication levels for a small part of the network and diagnosing who is involved in the outbreak. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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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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Murat Caner Testik 《Quality and Reliability Engineering International》2005,21(2):115-130
As a result of time series parameter estimation based on previous data, the probability content of residuals control charts may vary when standard control limits are used. In this paper, we consider the AR(1) process with the autoregressive parameter being estimated from a sample of observations. The performance of the exponentially weighted moving average (EWMA) control chart for residuals is investigated. Modified control limits that account for the uncertainty in the parameter estimate are provided. Comparisons through simulation signify the importance of the modified control limits. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献