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A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes
by
Mamzeridou, Eftychia
, Rakitzis, Athanasios C.
in
attributes control chart
/ average run length count data
/ Binomial distribution
/ Control charts
/ Control limits
/ expected average run length
/ inflated Poisson distribution
/ Markov chains
/ Markov processes
/ Monitoring
/ Probability distribution
/ Process parameters
/ Random variables
/ statistical process monitoring
2023
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A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes
by
Mamzeridou, Eftychia
, Rakitzis, Athanasios C.
in
attributes control chart
/ average run length count data
/ Binomial distribution
/ Control charts
/ Control limits
/ expected average run length
/ inflated Poisson distribution
/ Markov chains
/ Markov processes
/ Monitoring
/ Probability distribution
/ Process parameters
/ Random variables
/ statistical process monitoring
2023
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Do you wish to request the book?
A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes
by
Mamzeridou, Eftychia
, Rakitzis, Athanasios C.
in
attributes control chart
/ average run length count data
/ Binomial distribution
/ Control charts
/ Control limits
/ expected average run length
/ inflated Poisson distribution
/ Markov chains
/ Markov processes
/ Monitoring
/ Probability distribution
/ Process parameters
/ Random variables
/ statistical process monitoring
2023
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A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes
Journal Article
A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes
2023
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Overview
In this work, a control chart with multiple runs rules is proposed and studied in the case of monitoring inflated processes. Usually, Shewhart-type control charts for attributes do not have a lower control limit, especially when the in-control process mean level is very low, such as in the case of processes with a low number of defects per inspected unit. Therefore, it is not possible to detect a decrease in the process mean level. A common solution to this problem is to apply a runs rule on the lower side of the chart. Motivated by this approach, we suggest a Shewhart-type chart, supplemented with two runs rules; one is used for detecting decreases in process mean level, and the other is used for improving the chart’s sensitivity in the detection of small and moderate increasing shifts in the process mean level. Using the Markov chain method, we examine the performance of various schemes in terms of the average run length and the expected average run length. Two illustrative examples for the use of the proposed schemes in practice are also discussed. The numerical results show that the considered schemes can detect efficiently various shifts in process parameters in either direction.
Publisher
MDPI AG
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