New Single Variables Control Charts Based On The Double Ewma Statistics
In Statistical Process Control (SPC) monitoring situations, there is a tendency for both the process mean and process variability to shift simultaneously. Traditionally, two separate control charts, each for the mean and variance are used concurrently to monitor the process mean and process varia...
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Format: | Thesis |
Language: | English |
Published: |
2012
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Online Access: | http://eprints.usm.my/46102/1/TEH%20SIN%20YIN%2024.pdf |
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author | Teh, Sin Yin |
author_facet | Teh, Sin Yin |
author_sort | Teh, Sin Yin |
collection | USM |
description | In Statistical Process Control (SPC) monitoring situations, there is a tendency for
both the process mean and process variability to shift simultaneously. Traditionally,
two separate control charts, each for the mean and variance are used concurrently to
monitor the process mean and process variance. However, in many real life process
monitoring situations, a simultaneous control of the process mean and process
variance is necessary. This has motivated us to develop single DEWMA (called
Double Exponentially Weighted Moving Average) charts which are capable of
monitoring simultaneous shifts in both the process mean and process variance, when
the underlying distribution of the process is normal. The DEWMA statistics are
based on the approach of performing exponential smoothing twice on the original
statistics of the underlying process. The objective of this study is to propose three
single DEWMA charts, namely the DEWMA-Max (called the DEWMA maximum),
Max-DEWMA (called the maximum DEWMA) and SS-DEWMA (called the sum of
squares of DEWMA) charts. |
first_indexed | 2024-03-06T15:35:20Z |
format | Thesis |
id | usm.eprints-46102 |
institution | Universiti Sains Malaysia |
language | English |
last_indexed | 2024-03-06T15:35:20Z |
publishDate | 2012 |
record_format | dspace |
spelling | usm.eprints-461022020-02-06T01:57:01Z http://eprints.usm.my/46102/ New Single Variables Control Charts Based On The Double Ewma Statistics Teh, Sin Yin HD28-70 Management. Industrial Management In Statistical Process Control (SPC) monitoring situations, there is a tendency for both the process mean and process variability to shift simultaneously. Traditionally, two separate control charts, each for the mean and variance are used concurrently to monitor the process mean and process variance. However, in many real life process monitoring situations, a simultaneous control of the process mean and process variance is necessary. This has motivated us to develop single DEWMA (called Double Exponentially Weighted Moving Average) charts which are capable of monitoring simultaneous shifts in both the process mean and process variance, when the underlying distribution of the process is normal. The DEWMA statistics are based on the approach of performing exponential smoothing twice on the original statistics of the underlying process. The objective of this study is to propose three single DEWMA charts, namely the DEWMA-Max (called the DEWMA maximum), Max-DEWMA (called the maximum DEWMA) and SS-DEWMA (called the sum of squares of DEWMA) charts. 2012-02 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/46102/1/TEH%20SIN%20YIN%2024.pdf Teh, Sin Yin (2012) New Single Variables Control Charts Based On The Double Ewma Statistics. PhD thesis, Universiti Sains Malaysia. |
spellingShingle | HD28-70 Management. Industrial Management Teh, Sin Yin New Single Variables Control Charts Based On The Double Ewma Statistics |
title | New Single Variables Control Charts
Based On The Double Ewma Statistics |
title_full | New Single Variables Control Charts
Based On The Double Ewma Statistics |
title_fullStr | New Single Variables Control Charts
Based On The Double Ewma Statistics |
title_full_unstemmed | New Single Variables Control Charts
Based On The Double Ewma Statistics |
title_short | New Single Variables Control Charts
Based On The Double Ewma Statistics |
title_sort | new single variables control charts based on the double ewma statistics |
topic | HD28-70 Management. Industrial Management |
url | http://eprints.usm.my/46102/1/TEH%20SIN%20YIN%2024.pdf |
work_keys_str_mv | AT tehsinyin newsinglevariablescontrolchartsbasedonthedoubleewmastatistics |