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Journal ArticleDOI

Effects of correlation on fraction non-conforming statistical process control procedures

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TLDR
In this paper, the authors examined the control procedures based on the conforming unit run lengths applied to near-zero-defect processes in the presence of serial correlation and derived control limits.
Abstract
High-yield production processes that involve a low fraction non-conforming are becoming more common, and the limitations of the standard control charting procedures for such processes are well known. This paper examines the control procedures based on the conforming unit run lengths applied to near-zero-defect processes in the presence of serial correlation. Using a correlation binomial model, a few control schemes are investigated and control limits are derived. The results reduce to the traditional case when the measurements are independent. However, it is shown that the false alarm rate cannot be reduced to below the amount of serial correlation present in the process.

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Citations
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Journal ArticleDOI

SPC Procedures for Monitoring Autocorrelated Processes

TL;DR: The aim of this paper is to present, to apply and to evaluate control charts that are designed to account for autocorrelation.
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A Review and perspective on surveillance of Bernoulli processes

TL;DR: This expository paper reviews the methods implemented forBernoulli processes in health-related monitoring, offers advice to practitioners and presents a comprehensive literature review for researchers.
Journal ArticleDOI

A markov-binomial distribution

TL;DR: In this paper, the authors studied the number of successes of a Markov Chain with binomial and negative binomial distributions and proved a central limit theorem for Sn and provided conditions under which the distribution of Sn can be approximated by a Poisson type of distribution.
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Statistical process control for monitoring scheduling performance—addressing the problem of correlated data

TL;DR: The feasibility of monitoring flow time in a single processor model using control charts is studied using simulation and the need for approaches that are robust with respect to data correlation and lack of normality is shown to be an essential requirement.
Journal ArticleDOI

Control charts for monitoring the autocorrelated process parameters: a literature review

TL;DR: This paper provides a survey and brief summary of the work on the development of the control charts for variables to monitor the mean and dispersion for autocorrelated data.
References
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Journal ArticleDOI

Run-Length Distributions of Special-Cause Control Charts for Correlated Processes

TL;DR: In this paper, run-length distributions of the special cause control chart were derived for correlated observations, given that the assignable cause to be detected is a shift in the process mean.
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The use of a correlated binomial model for the analysis of certain toxicological experiments.

TL;DR: A type of correlated binomial model is proposed for use in certain toxicological experiments with laboratory animals where the outcome of interest is the occurrence of dead or malformed fetuses in a litter.
Journal Article

Detecting a shift in fraction nonconforming using runlength control charts with 100% inspection

TL;DR: When 100% inspection in the order of production is in progress, an alternative approach to the p-chart or the Poisson-based CUSUM chart is to monitor the lengths of runs of conforming items between successive nonconforming items.
Journal ArticleDOI

Detecting a Shift in Fraction Nonconforming Using Run-Length Control Charts with 100% Inspection

TL;DR: When 100% inspection in the order of production is in progress, an alternative approach to the p-chart or the Poisson-based CUSUM chart is to monitor the lengths of runs of conforming items between successive nonconforming items.
Journal ArticleDOI

Two Generalizations of the Binomial Distribution

TL;DR: In this article, the sum of k independent and identically distributed (0, 1) variables has a binomial distribution and two distinct generalizations are obtained, depending on whether the "multiplicative" or "additive" definition of interaction for discrete variables is used.
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