共查询到20条相似文献,搜索用时 15 毫秒
1.
Sudarat Nidsunkid John J. Borkowski Kamon Budsaba 《Quality and Reliability Engineering International》2017,33(8):2563-2576
A multivariate Shewhart and a multivariate exponentially weighted moving average control charts are types of multivariate control charts for monitoring the mean vector. For those control charts, a multivariate normal distribution is an important assumption that is used to describe a behavior of a set of quality characteristics of interest. This research explores the sensitivity of average run lengths and standard deviation of run lengths for the multivariate Shewhart and the multivariate exponentially weighted moving average control charts when the normality assumption is incorrect. 相似文献
2.
Zhang Wu 《Quality and Reliability Engineering International》1997,13(2):59-60
This communication addresses the problem of comparing the effectiveness of different control-charting schemes. The measure of average unit run length (AURL) is used to compare the effectiveness of the x-bar charts and the R charts with different sampling frequencies and different sample sizes. Since the trade-off between the frequency of false alarm and the detecting effectiveness is the most critical issue in the design of the control charts, we adjust the control limits of the charts in order to conduct the fair comparisons based on equal frequency of false alarm. © 1997 by John Wiley & Sons, Ltd. 相似文献
3.
Galal M. Abdella Khalifa N. Al‐Khalifa Sangahn Kim Myong K. Jeong Elsayed A. Elsayed Abdel Magid Hamouda 《Quality and Reliability Engineering International》2017,33(3):565-578
High‐dimensional applications pose a significant challenge to the capability of conventional statistical process control techniques in detecting abnormal changes in process parameters. These techniques fail to recognize out‐of‐control signals and locate the root causes of faults especially when small shifts occur in high‐dimensional variables under the sparsity assumption of process mean changes. In this paper, we propose a variable selection‐based multivariate cumulative sum (VS‐MCUSUM) chart for enhancing sensitivity to out‐of‐control conditions in high‐dimensional processes. While other existing charts with variable selection techniques tend to show weak performances in detecting small shifts in process parameters due to the misidentification of the ‘faulty’ parameters, the proposed chart performs well for small process shifts in identifying the parameters. The performance of the VS‐MCUSUM chart under different combinations of design parameters is compared with the conventional MCUSUM and the VS‐multivariate exponentially weighted moving average control charts. Finally, a case study is presented as a real‐life example to illustrate the operational procedures of the proposed chart. Both the simulation and numerical studies show the superior performance of the proposed chart in detecting mean shift in multivariate processes. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
4.
Saeed Maghsoodloo Samira Shirzaei 《Quality and Reliability Engineering International》2021,37(5):2098-2109
5.
R. Noorossana A. Vaghefi M. Dorri 《Quality and Reliability Engineering International》2011,27(4):425-436
In some statistical process control (SPC) applications, it is assumed that a quality characteristic or a vector of quality characteristics of interest follows a univariate or multivariate normal distribution, respectively. However, in certain applications this assumption may fail to hold and could lead to misleading results. In this paper, we study the effect of non‐normality when the quality of a process or product is characterized by a linear profile. Skewed and heavy‐tailed symmetric non‐normal distributions are used to evaluate the non‐normality effect numerically. The results reveal that the method proposed by Kimtextitet al. (J. Qual. Technol. 2003; 35 :317–328) can be designed to be robust to non‐normality for both highly skewed and heavy‐tailed distributions. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
6.
The performance of a control chart is completely characterized by its run length distribution. Quality practitioners usually do not have access to the run length distribution but rely on the average run length (ARL) to design and evaluate the performance of an exponentially weighted moving average (EWMA) control chart. This article presents a web-based tool that provides users easy access to the Phase 2 (online or monitoring phase) run length distribution for a two-sided EWMA control chart with known parameters. The web-based tool calculates the run length distribution, percentiles of the run length distribution, as well as the mean (ARL) and variance (VRL) of the run length distribution. Additional functionality of the web-based tool includes plotting the run length distribution functions, building tables of the quantiles of the run length distribution, finding the smoothing parameter (λ) for an EWMA control chart for fixed control limit that satisfies ARL, VRL or percentile performance, and finding the control chart limit (k) for an EWMA control chart that satisfies ARL, VRL, or percentile performance. This tool and these techniques enable quality practitioners to better design and evaluate EWMA control charts. 相似文献
7.
Michael B. C. Khoo 《Quality Engineering》2004,17(1):109-118
In this article a new control chart which enables a simultaneous monitoring of both the process mean and process variance of a multivariate data will be proposed. A thorough discussion in identifying whether the process mean or variability shifts is also given. Simulation studies will be performed to study the performance of the new chart by means of its average run length (ARL) profiles. Numerous examples are also given to show how the new chart is put to work in real situations. 相似文献
8.
Hafiz Zafar Nazir Muhammad Riaz Ronald J. M. M. Does 《Quality and Reliability Engineering International》2015,31(3):369-379
Process monitoring through control charts is a quite popular practice in statistical process control. From a statistical point of view, a superior control chart is one that has an efficient design structure, but having resistance against unusual situations is of more practical importance. To have a compromise between the statistical and practical purposes, a natural desire is to have a control chart that can serve both purposes simultaneously in a good capacity. This study is planned for the same objective focusing on monitoring the dispersion parameter by using a Cumulative Sum (CUSUM) control chart scheme. We investigate the properties of the design structure of different control charts based on some already existing estimators as well as some new robust dispersion estimators. By evaluating the performance of these estimators‐based CUSUM control charts in terms of average run length, we identify those charts that are more capable to make a good compromise between the aforementioned purposes in terms of statistical and practical needs. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
9.
An efficient alternative to the S control chart for detecting shifts of small magnitude in the process variability using a moving average based on the sample standard deviation s statistic is proposed. Control limit factors are derived for the chart for different values of sample size and span w. The performance of the moving average S chart is compared to the S chart in terms of average run length. The result shows that the performance of moving average S chart for varying values of w outweigh those of the S chart for small and moderate shifts in process variability. 相似文献
10.
Kashinath Chatterjee Christos Koukouvinos Angeliki Lappa 《Quality and Reliability Engineering International》2021,37(6):2423-2457
Control charts are widely known quality tools used to detect and control industrial process deviations in statistical process control. In the current paper, we propose a new single memory-type control chart, called the sum of squares triple exponentially weighted moving average control chart (referred as SS-TEWMA chart), that simultaneously detects shifts in the process mean and/or process dispersion. The run length performance of the proposed SS-TEWMA control chart is compared with that of the sum of squares EWMA, sum of squares double EWMA, sum of squares generally weighted moving average, and sum of squares double generally weighted moving average, control charts, through Monte Carlo simulations. The comparisons indicate that the proposed chart is more efficient, than the competing ones, in detecting small shifts in the process mean and/or variability for most of the considered scenarios, while it has comparable performance for some others in identifying large shifts in the process mean and small to large shifts in the process variability. Finally, two illustrative examples are provided to explain the application of the SS-TEWMA control chart. 相似文献
11.
Vasileios Alevizakos Christos Koukouvinos 《Quality and Reliability Engineering International》2020,36(1):88-111
The zero-inflated Poisson (ZIP) distribution is an extension of the ordinary Poisson distribution and is used to model count data with an excessive number of zeros. In ZIP models, it is assumed that random shocks occur with probability p, and upon the occurrence of random shock, the number of nonconformities in a product follows the Poisson distribution with parameter λ. In this article, we study in more detail the exponentially weighted moving average control chart based on the ZIP distribution (regarded as ZIP-EWMA) and we also propose a double EWMA chart with an upper time-varying control limit to monitor ZIP processes (regarded as ZIP-DEWMA chart). The two charts are studied to detect upward shifts not only in each parameter individually but also in both parameters simultaneously. The steady-state performance and the performance with estimated parameters are also investigated. The performance of the two charts has been evaluated in terms of the average and standard deviation of the run length, and compared with Shewhart-type and CUSUM schemes for ZIP distribution, it is shown that the proposed chart is very effective especially in detecting shifts in p when λ remains in control (IC) and in both parameters simultaneously. Finally, one real example is given to display the application of the ZIP charts on practitioners. 相似文献
12.
Olatunde Adebayo Adeoti Sunday Olawale Koleoso 《Quality and Reliability Engineering International》2020,36(6):2170-2186
Several modifications and enhancements to control charts in increasing the performance of small and moderate process shifts have been introduced in the quality control charting techniques. In this paper, a new hybrid control chart for monitoring process location is proposed by combining two homogeneously weighted moving average (HWMA) control charts. The hybrid homogeneously weighted moving average (HHWMA) statistic is derived using two smoothing constants λ1 and λ2 . The average run length (ARL) and the standard deviation of the run length (SDRL) values of the HHWMA control chart are obtained and compared with some existing control charts for monitoring small and moderate shifts in the process location. The results of study show that the HHWMA control chart outperforms the existing control charts in many situations. The application of the HHWMA chart is demonstrated using a simulated data. 相似文献
13.
Michael B. C. Khoo 《Quality Engineering》2003,16(1):75-85
A multivariate exponentially weighted moving average (MEWMA) control chart is used for fast detection of small shifts in multivariate statistical quality control. However, for ease of computation, the MEWMA control chart statistics are computed based on the asymptotic form of their covariance matrix in most cases. Another reason that justifies the design of the MEWMA control chart using the asymptotic covariance matrix is that the chart will be insensitive at start-up since processes are more likely to be away from the target value when the control scheme is initiated due to start-up problems. However, if initial out-of-control conditions are deemed important for quick detection, then the MEWMA statistics should be computed based on the exact covariance matrix, as it leads to a natural fast initial response for the MEWMA chart. It will also be shown in this paper the importance of computing the MEWMA statistics based on the exact form of their covariance matrix to further enhance the MEWMA control chart's sensitivity for detecting small shifts. The MEWMA statistics based on the asymptotic and the exact form of their covariance matrix will be referred to as the asymptotic and the exact MEWMA statistics, respectively. Plots and factors that simplify the design of the exact MEWMA control chart are also given. 相似文献
14.
Charles W. Champ Francisco Aparisi 《Quality and Reliability Engineering International》2008,24(2):153-166
Two double sampling T2 charts are discussed. They only differ in how the second sample is used to suggest to the practitioner the state of the process. An optimal method using a genetic algorithm is given for designing these charts based on the average run length (ARL). An analytical method is used to determine run length performance of the chart. Comparisons are made with various other control charting procedures. Some recommendations are given. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
15.
Memory based control charts are developed as alternatives to the Shewhart charts for the detection of small sustaining process shifts. Among the widely used memory control charts are the EWMA (Exponentially Weighted Moving Average), CUSUM (Cumulative Sum), and moving average schemes. Relative to the CUSUM chart, the EWMA and moving average charts are quite basic. The EWMA chart uses a weighted average as the chart statistic while the time-weighted moving average chart is based on unweighted moving average. The moving average statistic of width w is simply the average of the w most recent observations. In this article, the use of one moving average control chart to monitor both process mean and variability. This new moving average chart is efficient in detecting both increases and decreases in mean and/or variability. 相似文献
16.
Abdul Haq Michael Boon Chong Khoo 《Quality and Reliability Engineering International》2019,35(6):1803-1825
A control chart is a simple yet powerful tool that is extensively adopted to monitor shifts in the process mean. In recent years, auxiliary‐information–based (AIB) control charts have received considerable attention as these control charts outperform their counterparts in monitoring changes in the process parameter(s). In this article, we integrate the conforming run length chart with the existing AIB double sampling (AIB DS) chart to propose an AIB synthetic DS chart for the process mean. The AIB synthetic DS chart also encompasses the existing synthetic DS chart. A detailed discussion on the construction, optimization, and evaluation of the run length profiles is provided for the proposed control chart. It is found that the optimal AIB synthetic DS chart significantly outperforms the existing AIB Shewhart, optimal AIB synthetic, and AIB DS charts in detecting various shifts in the process mean. An illustrative example is given to demonstrate the implementation of the existing and proposed AIB control charts. 相似文献
17.
XueLong Hu Philippe Castagliola 《Quality and Reliability Engineering International》2017,33(8):1873-1884
A common assumption for most control charts is the fact that the process parameters are supposed to be known or accurately estimated from Phase I samples. But, in practice, this is not a realistic assumption and the process parameters are usually estimated from a very limited number of samples that, in addition, may contain some outliers. Recently, a median chart with estimated parameters has been proposed to overcome these issues and it has been investigated in terms of the unconditional Average Run Length (ARL). As this median chart with estimated parameters does not take the “Phase I between‐practitioners” variability into account, in this paper, we suggest to revisit it using the Standard Deviation of the ARL as a measure of performance. The results show that this Standard Deviation of the ARL–based median chart actually requires a much larger amount of Phase I data than previously recommended to sufficiently reduce the variation in the chart performance. Due to the practical limitation of the number of the Phase I data, the bootstrap method is recommended as a good alternative approach to define new dedicated control chart parameters. 相似文献
18.
Nasir Abbas 《Quality and Reliability Engineering International》2020,36(1):403-413
Shewhart S2 control chart is one of the most commonly used tools to monitor the dispersion of a process. In this article, we evaluate the performance of S2 control chart when the unknown parameter is estimated from Phase-I samples. Average ARL and standard deviation of ARL metrics are used to evaluate the performance. In the first stage of the study, new control limit coefficients are derived so that the average ARL is equal to the pre-fixed ARL, ie, 370. Secondly, different proportion of outliers is contaminated into Phase-I samples, and the resulting elevated average ARL and standard deviation of ARL are measured. Finally, the application of Tukey's outlier detector is proposed with Phase-I samples so that the elevation caused by the outliers can be controlled and the average ARL can be pulled back close to the pre-fixed ARL. For illustration, the proposed procedures are applied to a data on compressive strength of parts manufactured by an injection molding process. 相似文献
19.
传统Shewhart-
20.
Nonparametric control charts provide a robust alternative in practice when the form of the underlying distribution is unknown. Nonparametric CUSUM (NPCUSUM) charts blend the advantages of a CUSUM with that of a nonparametric chart in detecting small to moderate shifts. In this paper, we examine efficient design and implementation of Phase II NPCUSUM charts based on exceedance (EX) statistics, called the NPCUSUM-EX chart. We investigate the choice of the order statistic from the reference (Phase I) sample that defines the exceedance statistic. We see that choices other than the median, such as the 75th percentile, can yield improved performance of the chart in certain situations. Furthermore, observing certain shortcomings of the average run-length, we use the median run-length as the performance metric. The NPCUSUM-EX chart is compared with the NPCUSUM-Rank chart based on the popular Wilcoxon rank-sum statistic. We also study the choice of the reference value, k, of the CUSUM charts. An illustration with real data is provided. 相似文献