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Detecting shifts in Conway–Maxwell–Poisson profile with deviance residual-based CUSUM and EWMA charts under multicollinearity
Monitoring profiles with count responses is a common situation in industrial processes and for a count distributed process, the...
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Improved control chart for statistical process control using combined X and delayed EWMA statistics
In this paper, we propose a new combination of X and EWMA charts in which we intentionally delay the EWMA statistic one lag to make it independent of...
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Control charts for measurement error models
We consider a linear measurement error model (MEM) with AR(1) process in the state equation which is widely used in applied research. This MEM could...
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The exponentiated exponentially weighted moving average control chart
Memory-type control charts are widely used for monitoring small to moderate shifts in the process parameter(s). In the present article, we present an...
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Detecting Disease Outbreak Regions Using Multiple Data Streams
A novel approach for biosurveillance using multiple data streams is presented. The proposed method is computationally simple, has rapid detection...
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Control Charts
In the subject of statistical quality controlStatistical quality control, the word control bears a special technical meaning. A manufacturing process...
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Monitoring and Comparing Air and Green House Gases Emissions of Various Countries
The quality assurance of the earth-atmosphere system, which runs primarily to temperature variations and other disturbances of the earth’s climate,...
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On the Calculation of the ARL for Beta EWMA Control Charts
Accurate calculation of the Average Run Length (ARL) for exponentially weighted moving average (EWMA) charts might be a tedious task. The omnipresent...
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Economic design of memory-type control charts: The fallacy of the formula proposed by Lorenzen and Vance (1986)
Memory-type statistical control charts, such as exponentially weighted moving average (EWMA) and cumulative sum (CUSUM), are broadly-used statistical...
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Run and Scan Rules in Statistical Process Monitoring
In this paper, we provide an overview of the use of run and scan rules in statistical process monitoring. Although we focus on control charts,...
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Monitoring mean of INAR(1) process with discrete mixture exponential innovations
This paper presents a discrete counterpart of the mixture exponential distribution, namely discrete mixture exponential distribution, by utilizing...
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Advanced Methods of Statistical Process Control
Following Chap. 2 , we present in this chapter more advanced methods of statistical process control. We...
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ARL-Unbiased CUSUM Schemes to Monitor Binomial Counts
Counted output, such as the number of defective items per sample, is often assumed to have a marginal binomial distribution. The integer and...
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Control charts for monitoring the median in non-negative asymmetric data
Control charts are commonly used for monitoring the mean of processes. However, there are practical applications in which asymmetric data are the...
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Quantile-based control charts for poisson and gamma distributed data
In terms of statistical process control (SPC), the probability distributions of the quality characteristics are critical in detecting changes in the...
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Designing robust modified R control charts for asymmetric distributions under ranked set and median ranked set sampling
Presence of outliers or contamination in the process control affect the construction of quality control limits badly. Therefore, more attention is to...
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Simultaneous monitoring of origin and scale in left-bounded processes via depth
A novel notion of depth for the origin and scale of a distribution with left-bounded support, like those modelling lifetime data, is presented. This...
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The Scan Statistic for Multidimensional Data and Social Media Applications
This chapter reviews the literature on the scan statistic with particular emphasis on its application. The chapter considers the application of the...
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Risk-Adjusted Control Charts: Theory, Methods, and Applications in Health
Control charts, the most popular tool of statistical process control, appeared in the literature to ensure that an industrial process is operating...
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Use of Conditional False Alarm Metric in Statistical Process Monitoring
The conditional false alarm rate (CFAR) at a particular time is the probability of a false alarm for an assumed in-control process at that time...