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Adaptive EWMA Control Charts with a Time Varying Smoothing Parameter [PDF]
, 2015 It is known that time-weighted charts like EWMA or CUSUM are designed to be optimal to detect a specific shift. If they are designed to detect, for instance, a very small shift, they can be inefficient to detect moderate or large shifts.
Sánchez, Ismael +1 more
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General adapted‐threshold monitoring in discrete environments and rules for imbalanced classes
Statistica Neerlandica, Volume 79, Issue 1, February 2025.Having in mind applications in statistics and machine learning such as individualized care monitoring, or watermark detection in large language models, we consider the following general setting: When monitoring a sequence of observations, Xt, there may be additional information, Zt, on the environment which should be used to design the monitoring ...
Ansgar Steland +2 more
wiley +1 more source
A new procedure for monitoring the range and standard deviation of a quality characteristic [PDF]
The Shewhart and the Bonferroni-adjustment R and S chart are usually applied to monitor the range and the standard deviation of a quality characteristic. These charts are used to recognize the process variability of a quality characteristic.
Kiani, Mehdi +2 more
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A control chart for monitoring image processes based on convolutional neural networks
Statistica Neerlandica, Volume 79, Issue 1, February 2025.In this paper, the problem of monitoring image processes with spatially correlated pixels over time is considered. An exponentially weighted moving average (EWMA) control chart for monitoring such processes based on a convolutional neural network (CNN) is proposed.
Yarema Okhrin +2 more
wiley +1 more source
Zero-Defect Manufacturing in the Industry 4.0 Era: A Hybrid Approach to Detecting Quality Shifts
ITEGAM-JETIAThanks to the emergence of the Industry 4.0 paradigm, the idea of Zero-Defect Manufacturing (ZDM) has now been claimed to be possible. The ZDM is based on four strategies: detecting, repairing, predicting, and preventing.
Rafael Kovalechyn +2 more
doaj +1 more source
Iteckne, 2018 One of the most significant aspects to improve the quality of the processes is to avoid the increase of the variability, so it is important the continuous monitoring of the quality feature, which allows to know its condition and behavior over time.
Roberto José Herrera-Acosta +2 more
doaj +1 more source
Multivariate Statistical Process Control Charts: An Overview [PDF]
In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate ...
Bersimis, Sotiris +2 more
core +1 more source
Effects of the two-component measurement error model on X control charts
Statistica, 2013 The statistical properties of Shewhart control charts are known to be highly sensitive to measurement errors. The statistical model relating the measured value to the true, albeit not observable, value of a product characteristic, is usually Gaussian and
Daniela Cocchi, Michele Scagliarini
doaj +1 more source
Power functions of the Shewhart control chart
Journal of Physics: Conference Series, 2013 The Shewhart control chart is used to check for a lack of control (a shift in the process). However it is insensitive to small shifts. To increase the sensitivity of the Shewhart control chart, some actions can be taken. These include reducing the width of the control limits, increasing the subgroup size to reduce the variance of the sample mean and ...
openaire +1 more source
A general class of entropy based control charts
, 2017 We introduce a new class of Shewhart control charts, namely the phi-chart. This new class is based on the cumulative paired phi-divergence that generalizes both the cumulative (residual) entropy and the differential entropy.
Konopik, Jens, Mangold, Benedikt
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