Monitoring multivariate quality variables or data streams remains an important and challenging problem in statistical process control (SPC). Although the multivariate SPC has been extensively studied in the literature, designing distribution-free control schemes are still challenging and yet to be addressed well. This paper develops a new nonparametric methodology for monitoring location parame...

Most robust control charts in the literature are for monitoring process location parameters, such as mean or median, rather than process dispersion parameters.This paper develops a new robust control chart by integrating a two-sample nonparametric test into the effective change-point model. Our proposed chart is easy in computation, convenient to use, and very powerful in detecting process disp...

CCC-r control chart is a monitoring technique for high yield processes. It is based on the analysis of the number of inspected items until observing a specific number of defective items.  One of the assumptions in implementing CCC-r chart that has a significant effect on the design of the control chart is that the inspection is perfect. However, in reality, due to the multiple reasons, the...

The most popular tool used in the industry for monitoring a process is the Shewhart control chart. The major disadvantage of the Shewhart control chart is that it is not very efficient in detecting small process average shifts. To increase the sensitivity of Shewhart control charts to small shifts additional supplementary runs rules has been suggested. In this paper we introduce and study the m...

Nonparametric control charts can provide a robust alternative in practice to the data analyst when there is a lack of knowledge about the underlying distribution. A nonparametric exponentially weighted moving average (NPEWMA) control chart combines the advantages of a nonparametric control chart with the better shift detection properties of a traditional EWMA chart. A NPEWMA chart for the media...

Usually, in monitoring schemes the nominal value of the process parameter is assumed known. However, this assumption is violated owing to costly sampling and lack of data particularly in healthcare systems. On the other hand, applying a fixed control limit for the risk-adjusted Bernoulli chart causes to a variable in-control average run length performance for patient populations with dissimilar...

For product manufacturing, control charts are important tools. Different types of control charts are used to monitor different measures of product characteristics. Among the numerous charts, the popular one is the Hotelling’s T 2 chart. It is designed while taking into account the most sensitive measures such as sample covariance matrix and sample mean vector. However, the chart becomes ineffec...

This working paper series is intended to facilitate discussion and encourage the exchange of ideas. Inclusion here does not preclude publication elsewhere. It is the original work of the author(s) and subject to copyright regulations. ABSTRACT We believe that conflicting decision signals resulting from examining Shewhart Mean and Variability Control Charts produce undesirable consequences. Ther...

Call it the department chair’s dilemma: How do you get a swarm of independently minded minions moving in concert toward some useful goal? The problem may be inherently insoluble in a professorial setting, in part because the notion of academic motion is purely metaphoric. But encouraging signs of progress have emerged for a more literal analog. Researchers in control theory are perfecting a rep...

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