A Study Of Exponentially Weighted Moving Average (EWMA) Methodologies
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Date
1993-12
Authors
Lee, Toh Tong
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Abstract
This thesis concerns the use of the EHHA chart, an
alternative to the Shewhart and Cumulative Sum (CUSUM)
charts, for detecting a change in a process. We have written
this thesis with two objectives in mind:
i) to review the control charting methodologies of
the EWMA control chart, and
ii) to suggest some additional enhancements that can
further enhance the EWMA chart.
In this thesis, we provide an overview of the EWMA
charts for the monitoring of the process mean and the
process variance. Enhancements to the EWMA given by various
authors for b~th the process mean and the process variance
are also discussed. While reviewing all the different
enhancements proposed by various authors, we will compare
each enhancement to the others which serve similar purposes
and try to summarize the similarities and differences
between these methods. The pros and cons of each of them
will also be discussed. We also show how the EWMA chart can
be constructed using the appropriate enhancements.Some general discussions on issues related to the EWMA
chart are also given. The discussion on the advantages and
weaknesses of the EWMA chart and a comparison of the EWMA
chart with the CUSUM chart will enable us to decide whether
or not to use the EWMA chart. We also include a brief
discussion on the use of the EWMA for a nonstationary
process, some possible directions for future research, and
current developments and prospects for the EWMA chart.
In addition to a review of some enhancements suggested
by various authors, we have also given some suggestions of
our own. For example, the plotting of residuals in
conjunction with an EWMA chart to detect large shifts in the
process mean or
more effective
any other abnormality, a method which is
in detecting a shift in the process mean
which causes a eduction in the dispersion, and a method for
determining when changes in the process mean start occurring
and the magnitudes of such changes.
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Keywords
Exponentially Weighted Moving Average (EWMA)