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Michael S. Saccucci

Other affiliations: Drexel University
Bio: Michael S. Saccucci is an academic researcher from Western Connecticut State University. The author has contributed to research in topics: CUSUM & Control chart. The author has an hindex of 11, co-authored 14 publications receiving 3631 citations. Previous affiliations of Michael S. Saccucci include Drexel University.

Papers
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Journal Article
TL;DR: The recognition that an EWMA control scheme can be represented as a Markov chain allows its properties to be evaluated more easily and completely than has previously been done.

1,624 citations

Journal ArticleDOI
TL;DR: In this article, the authors evaluate the properties of an exponentially weighted moving average (EWMA) control scheme used to monitor the mean of a normally distributed process that may experience shifts away from the target value.
Abstract: Roberts (1959) first introduced the exponentially weighted moving average (EWMA) control scheme. Using simulation to evaluate its properties, he showed that the EWMA is useful for detecting small shifts in the mean of a process. The recognition that an EWMA control scheme can be represented as a Markov chain allows its properties to be evaluated more easily and completely than has previously been done. In this article, we evaluate the properties of an EWMA control scheme used to monitor the mean of a normally distributed process that may experience shifts away from the target value. A design procedure for EWMA control schemes is given. Parameter values not commonly used in the literature are shown to be useful for detecting small shifts in a process. In addition, several enhancements to EWMA control schemes are considered. These include a fast initial response feature that makes the EWMA control scheme more sensitive to start-up problems, a combined Shewhart EWMA that provides protection against both larg...

1,380 citations

Journal ArticleDOI
TL;DR: The variable sampling interval (VSI) CUSUM chart as mentioned in this paper uses short sampling intervals if there is an indication that the process mean may have shifted and long sampling intervals when there is no indication of a change in the mean.
Abstract: A standard cumulative sum (CUSUM) chart for controlling the process mean takes samples from the process at fixed-length sampling intervals and uses a control statistic based on a cumulative sum of differences between the sample means and the target value. This article proposes a modification of the standard CUSUM scheme that varies the time intervals between samples depending on the value of the CUSUM control statistic. The variable sampling interval (VSI) CUSUM chart uses short sampling intervals if there is an indication that the process mean may have shifted and long sampling intervals if there is no indication of a change in the mean. If the CUSUM statistic actually enters the signal region, then the VSI CUSUM chart signals in the same manner as the standard CUSUM chart. A Markov-chain approach is used to evaluate properties such as the average time to signal and the average number of samples to signal. Results show that the proposed VSI CUSUM chart is considerably more efficient than the standard CUS...

229 citations

Journal ArticleDOI
TL;DR: The use of non-constant sampling intervals has been of interest in quality control applications since it was first suggested for the "skip-lot sampling plan" of Dodge as discussed by the authors.
Abstract: The idea of using non-constant sampling intervals has been of interest in quality control applications since it was first suggested for the “skip-lot sampling plan” of Dodge. Recent interest has focused on the use of variable sampling interval (VSI) control schemes. VSI control schemes use a short sampling interval is given

189 citations

Journal ArticleDOI
TL;DR: In this paper, a FORTRAN computer program is given for the computation of average run lengths (ARLs) for exponentially weighted moving average (EWMA) and combined Shewhart-EWMA control schemes.
Abstract: A FORTRAN computer program is given for the computation of average run lengths (ARLs) for exponentially weighted moving average (EWMA) and combined Shewhart-EWMA control schemes. The program calculates zero-state and steady-state ARLs using the Markov c..

97 citations


Cited by
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Proceedings ArticleDOI
26 Aug 2001
TL;DR: An efficient algorithm for mining decision trees from continuously-changing data streams, based on the ultra-fast VFDT decision tree learner is proposed, called CVFDT, which stays current while making the most of old data by growing an alternative subtree whenever an old one becomes questionable, and replacing the old with the new when the new becomes more accurate.
Abstract: Most statistical and machine-learning algorithms assume that the data is a random sample drawn from a stationary distribution. Unfortunately, most of the large databases available for mining today violate this assumption. They were gathered over months or years, and the underlying processes generating them changed during this time, sometimes radically. Although a number of algorithms have been proposed for learning time-changing concepts, they generally do not scale well to very large databases. In this paper we propose an efficient algorithm for mining decision trees from continuously-changing data streams, based on the ultra-fast VFDT decision tree learner. This algorithm, called CVFDT, stays current while making the most of old data by growing an alternative subtree whenever an old one becomes questionable, and replacing the old with the new when the new becomes more accurate. CVFDT learns a model which is similar in accuracy to the one that would be learned by reapplying VFDT to a moving window of examples every time a new example arrives, but with O(1) complexity per example, as opposed to O(w), where w is the size of the window. Experiments on a set of large time-changing data streams demonstrate the utility of this approach.

1,790 citations

Journal ArticleDOI
TL;DR: In this article, a multivariate extension of the exponentially weighted moving average (EWMA) control chart is presented, and guidelines given for designing this easy-to-implement multivariate procedure.
Abstract: A multivariate extension of the exponentially weighted moving average (EWMA) control chart is presented, and guidelines given for designing this easy-to-implement multivariate procedure. A comparison shows that the average run length (ARL) performance of this chart is similar to that of multivariate cumulative sum (CUSUM) control charts in detecting a shift in the mean vector of a multivariate normal distribution. As with the Hotelling's χ2 and multivariate CUSUM charts, the ARL performance of the multivariate EWMA chart depends on the underlying mean vector and covariance matrix only through the value of the noncentrality parameter. Worst-case scenarios show that Hotelling's χ2 charts should always be used in conjunction with multivariate CUSUM and EWMA charts to avoid potential inertia problems. Examples are given to illustrate the use of the proposed procedure.

1,174 citations

Journal ArticleDOI
TL;DR: A review of the literature on control charts for multivariate quality control (MQC) is given, with a concentration on developments occurring since the mid-1980s as mentioned in this paper, where several recent articles that give methods for interpreting an out-of control signal on a multivariate control chart are analyzed and discussed.
Abstract: A review of the literature on control charts for multivariate quality control (MQC) is given, with a concentration on developments occurring since the mid-1980s. Multivariate cumulative sum (CUSUM) control procedures and a multivariate exponentially weighted moving average (EWMA) control chart are reviewed and recommendations are made regarding their use. Several recent articles that give methods for interpreting an out-of-control signal on a multivariate control chart are analyzed and discussed. Other topics such as the use of principal components and regression adjustment of variables in MQC, as well as frequently used approximations in MQC, are discussed.

696 citations

Journal ArticleDOI
TL;DR: An overview of current research on control charting methods for process monitoring and improvement and a historical perspective and ideas for future research are given.
Abstract: An overview is given of current research on control charting methods for process monitoring and improvement. A historical perspective and ideas for future research also are given. Research topics include: variable sample size and sampling interval met..

647 citations

Journal ArticleDOI
TL;DR: Control charts are developed assuming that the sequence of process observations to which they are applied are uncorrelated, but the presence of autocorrelation has a serious impact on quality.
Abstract: Traditionally, control charts are developed assuming that the sequence of process observations to which they are applied are uncorrelated. Unfortunately, this assumption is frequently violated in practice. The presence of autocorrelation has a serious i..

611 citations