共查询到20条相似文献，搜索用时 15 毫秒
1.
A closed-loop identification procedure for pure gain-plus noise processes is presented for a family of disturbances that model drift in a discrete-part manufacturing system. Tuning techniques for the identified disturbance are provided for proportional integral (PI)controllers. These include the particular case of exponentially weighted moving average controllers, popular in semiconductor manufacturing. Expressions are derived for the mean squared deviation of the quality characteristic and for the variance of the adjustments. An optimization model is presented that balances adjustment variance with output variance. The optimal trade-off solution for a constrained PI controller is shown to depend on the assumption of no drift. 相似文献
2.
Most research of run-to-run process control has been based on single-input and single-output processes with static input–output relationships. In practice, many complicated semiconductor manufacturing processes have multiple-input and multiple-output (MIMO) variables. In addition, the effects of previous process input recipes and output responses on the current outputs might be carried over for several process periods. Under these circumstances, using conventional controllers usually results in unsatisfactory performance. To overcome this, a complicated process could be viewed as dynamic MIMO systems with added general process disturbance and this article proposes a dynamic-process multivariate exponentially weighted moving average (MEWMA) controller to adjust those processes. The long-term stability conditions of the proposed controller are derived analytically. Furthermore, by minimizing the total mean square error (TMSE) of the process outputs, the optimal discount matrix of the proposed controller under vector IMA(1,?1) disturbance is derived. Finally, to highlight the contribution of the proposed controller, we also conduct a comprehensive simulation study to compare the control performance of the proposed controller with that of the single MEWMA and self-tuning controllers. On average, the results demonstrate that the proposed controller outperforms the other two controllers with a TMSE reduction about 32% and 43%, respectively. 相似文献
3.
Harriet Black Nembhard René Valverde‐Ventura 《Quality and Reliability Engineering International》2007,23(3):303-325
We investigate the monitoring of a process subject to minimum mean‐squared error feedback control using cumulative score (Cuscore) charts. Specifically, we design Cuscore statistics to discover spike, step, bump, and ramp signals hidden in non‐stationary disturbance for feedback‐controlled processes. We develop the adjustment and monitoring policies for combinations of process dynamics, disturbance, and signal that are practical in industry. We also address issues of detection probabilities and distributions using simulation. A manufacturing case study is used to illustrate the utility of the Cuscore approach. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
4.
The double exponentially weighted moving average (EWMA) controller is a popular algorithm for on-line quality control of semiconductor manufacturing processes. The performance of the closed-loop system hinges on the adequacy of the two weight parameters of the double EWMA equations. In 2004, Su and Hsu presented an approach based on the neural technique for ‘on-line’ tuning the weight of the single EWMA equation in the single-input single-output (SISO) system. The present paper extends the neural network on-line tuning scheme to the double EWMA controller for the non-squared multiple-input multiple-output (MIMO) system, and validates the control performance by means of a simulated chemical–mechanical planarization (CMP) process in semiconductor manufacturing. Both linear and non-linear equipment models are considered to evaluate the proposed controller, coupling with the deterministic drift, the Gaussian noise and the first-order integrated moving average (IMA) disturbance. It has been shown from a variety of simulation studies that the proposed method exhibits quite competitive control performance as compared with the previous control system. The other merit of the proposed approach is that the tuning system, if sufficient training in a neural network is available, can be practicably applied to complex semiconductor processes without undue difficulty. 相似文献
5.
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
6.
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
7.
《技术计量学》2013,55(3):208-219
Several forecast-based monitoring methods have been developed for autocorrelated data. One effective method is to use the forecasts based on the exponentially weighted moving average (EWMA). However, during the transition period of dynamic systems, the forecast-based monitoring procedure becomes inadequate due to its use of constant time series model parameters. In this article we present an adaptive forecast-based monitoring approach that performs well on dynamic systems. We examine two competing procedures: the adaptive time series model and the adaptive EWMA. We use a plastic extrusion process with first-order dynamics to illustrate the application of these two procedures, and we also evaluate the performance of the two procedures via simulation. 相似文献
8.
Nien Fan Zhang 《技术计量学》2013,55(1):24-38
In the statistical process control environment, a primary method to deal with autocorrelated data is the use of a residual chart. Although this methodology has the advantage that it can be applied to any autocorrelated data, it needs some modeling effort in practice. In addition, the detection capability of the residual chart is not always great. This article proposes a statistical control chart for stationary process data. It is simple to implement, and no modeling effort is required. Comparisons are made among the proposed chart, the residual chart, and other charts. When the process autocorrelation is not very strong and the mean changes are not large, the new chart performs better than the residual chart and the other charts. 相似文献
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11.
Ken Nishina 《Quality and Reliability Engineering International》1992,8(6):537-541
ISO/DIS 7870 has presented the cumulative sum chart, the moving average chart, and the exponentially weighted moving average chart as control charts using accumulated data. In this paper, we compare the three control charts in terms of change-point estimation. We show the probability distribution, the bias and the mean square error of the change-point estimators using a Markov process and Monte Carlo simulation. These control charts have almost equivalent performances based on average run length considerations when parameters of each control chart are set appropriately. However, from the viewpoint of change-point estimation we recommend the CUSUM chart. 相似文献
12.
Nasir Abbas 《Quality and Reliability Engineering International》2015,31(4):719-720
In the category of memory‐type control charts, progressive mean control chart was proposed recently, for monitoring the process location. Here we show, through the derivation, that the plotting statistic for the progressive mean control chart becomes a special case of exponentially weighted moving average when the sensitivity parameter becomes reciprocal of the sample number. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
13.
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
14.
The use of varying sample size monitoring techniques for Poisson count data has drawn a great deal of attention in recent years. Specifically, these methods have been used in public health surveillance, manufacturing, and safety monitoring. A number of approaches have been proposed, from the traditional Shewhart charts to cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) methods. It is convenient to use techniques based on statistics that are invariant to the units of measurement since in most cases these units are arbitrarily selected. A few of the methods reviewed in our expository article are not inherently invariant, but most are easily modified to be invariant. Most importantly, if methods are invariant to the choice of units of measurement, they can be applied in situations where the in-control Poisson mean varies over time, even if there is no associated varying sample size. Several examples are discussed to highlight the promising uses of invariant Poisson control charting methods in this much broader set of applications, which includes risk-adjusted monitoring in healthcare, public health surveillance, and monitoring of continuous time nonhomogeneous Poisson processes. A new chart design method based on extensive online simulation is highlighted. 相似文献
15.
Yi Dai Yunzhao Luo Zhonghua Li Zhaojun Wang 《Quality and Reliability Engineering International》2011,27(7):877-884
We propose a new multivariate CUSUM control chart, which is based on self adaption of its reference value according to the information from current process readings, to quickly detect the multivariate process mean shifts. By specifying the minimum magnitude of the process mean shift in terms of its non‐centrality parameter, our proposed control chart can achieve an overall performance for detecting a particular range of shifts. This adaptive feature of our method is based on two EWMA operators to estimate the current process mean level and make the detection at each step be approximately optimal. Moreover, we compare our chart with the conventional multivariate CUSUM chart. The advantages of our control chart detection for range shifts over the existing charts are greatly improved. The Markovian chain method, through which the average run length can be computed, is also presented. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
16.
Vasileios Alevizakos Kashinath Chatterjee Christos Koukouvinos 《Quality and Reliability Engineering International》2021,37(8):3395-3416
Parametric (or traditional) control charts are based on the assumption that the quality characteristic of interest follows a specific distribution. However, in many applications, there is a lack of knowledge about the underlying distribution. To this end, nonparametric (or distribution-free) control charts have been developed in recent years. In this article, a nonparametric double homogeneously weighted moving average (DHWMA) control chart based on the sign statistic is proposed for monitoring the location parameter of an unknown and continuous distribution. The performance of the proposed chart is measured through the run-length distribution and its associated characteristics by performing Monte Carlo simulations. The DHWMA sign chart is compared with other nonparametric sign charts, such as the homogeneously weighted moving average, generally weighted moving average (GWMA), double GWMA, and triple exponentially weighted moving average sign charts, as well as the traditional DHWMA chart. The results indicate that the proposed chart performs just as well as and in some cases better than its competitors, especially for small shifts. Finally, two examples are provided to show the application and implementation of the proposed chart. 相似文献
17.
In‐Jun Jeong Kwang‐Jae Kim Dennis K. J. Lin 《Quality and Reliability Engineering International》2010,26(5):417-430
Dual response surface optimization considers the mean and the variation simultaneously. The minimization of mean‐squared error (MSE) is an effective approach in dual response surface optimization. Weighted MSE (WMSE) is formed by imposing the relative weights, (λ, 1?λ), on the squared bias and variance components of MSE. To date, a few methods have been proposed for determining λ. The resulting λ from these methods is either a single value or an interval. This paper aims at developing a systematic method to choose a λ value when an interval of λ is given. Specifically, this paper proposes a Bayesian approach to construct a probability distribution of λ. Once the distribution of λ is constructed, the expected value of λ can be used to form WMSE. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
18.
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-
19.
Vasileios Alevizakos Christos Koukouvinos Kashinath Chatterjee 《Quality and Reliability Engineering International》2020,36(7):2441-2458
Most control charts have been developed based on the actual distribution of the quality characteristic of interest. However, in many applications, there is a lack of knowledge about the process distribution. Therefore, in recent years, nonparametric (or distribution-free) control charts have been introduced for monitoring the process location or scale parameter. In this article, a nonparametric double generally weighted moving average control chart based on the signed-rank statistic (referred as DGWMA-SR chart) is proposed for monitoring the location parameter. We provide the exact approach to compute the run-length distribution, and through an extensive simulation study, we compare the performance of the proposed chart with existing nonparametric charts, such as the exponentially weighted moving average signed-rank (EWMA-SR), the generally weighted moving average signed-rank (GWMA-SR), the double exponentially weighted moving average signed-rank (DEWMA-SR), and the double generally weighted moving average sign (DGWMA-SN) charts, as well as the parametric DGWMA-
20.
Maonatlala Thanwane Saddam Akber Abbasi Jean-Claude Malela-Majika Muhammad Aslam Sandile Charles Shongwe 《Quality and Reliability Engineering International》2021,37(6):2568-2586
Fast initial response (FIR) features are generally used to improve the sensitivity of memory-type control charts by shrinking time-varying control limits in the earlier stage of the monitoring regime. This paper incorporates FIR features to increase the sensitivity of the homogeneously weighted moving average (HWMA) monitoring schemes with and without measurement errors under constant as well as linearly increasing variance scenarios. The robustness and the performance of the HWMA monitoring schemes are investigated in terms of numerous run-length properties assuming that the underlying process parameters are known and unknown. It is found that the FIR features improves the performance of the HWMA monitoring scheme as compared to the standard no FIR feature HWMA scheme, and at the same time, it is observed that the simultaneous use of a recently proposed FIR feature and multiple measurements significantly reduces the negative effect of measurement errors. An illustrative example on the volume of milk in bottles is used to demonstrate a real-life application. 相似文献