Abstract
This paper describes a method supporting recognition of unnatural patterns on a Shewhart X chart by analysis of its frequency distribution. It has been implemented as a program that simulates data from a statistically controlled process as well as from a process affected by patterns. The following patterns are simulated: sudden shift, trend, stratification, systematic variable, cycle and mixture
A user has the possibility to set up both the parameters of the process under statistical control and the parameters of a pattern. Then, he/she can observe static X and R charts or run dynamical simulation. During the simulation, it is possible to choose the moment when the pattern begins and when the pattern ends
The further development of the method is the implementation of a trained neural network for recognition of the pattern.
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References
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© 2001 Springer-Verlag Berlin Heidelberg
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Nieckula, J. (2001). Frequency Distribution Supporting Recognition of Unnatural Patterns on Shewhart X-bar Chart. In: Lenz, HJ., Wilrich, PT. (eds) Frontiers in Statistical Quality Control 6. Frontiers in Statistical Quality Control, vol 6. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57590-7_8
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DOI: https://doi.org/10.1007/978-3-642-57590-7_8
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-1374-6
Online ISBN: 978-3-642-57590-7
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