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Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method

A key assumption in traditional statistical process control (SPC) technique is based on the requirement that observations or time series data are normally and independently distributed. The presences of a serial autocorrelation results in a number of problems, including an increase in the type I err...

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Main Authors: Mat Desa, Nor Hasliza, Jemain, Abdul Aziz
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
QA Mathematics
Online Access:http://repo.uum.edu.my/19043/1/AIPCP%20157%202014%201049-1054.pdf
http://repo.uum.edu.my/19043/
http://doi.org/10.1063/1.4858792
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spelling my.uum.repo.190432016-11-09T08:11:42Z http://repo.uum.edu.my/19043/ Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method Mat Desa, Nor Hasliza Jemain, Abdul Aziz QA Mathematics A key assumption in traditional statistical process control (SPC) technique is based on the requirement that observations or time series data are normally and independently distributed. The presences of a serial autocorrelation results in a number of problems, including an increase in the type I error rate and thereby increase the expected number of false alarm in the process observation.However, the independency assumption is often violated in practice due to the influence of serial correlation in the observation. Therefore, the aim of this paper is to demonstrate with the hospital admission data, the influence of serial correlation on the statistical control charts. The trend free pre-whitening (TFPW) method has been used and applied as an alternative method to obtain residuals series which are statistically uncorrelated to each other.In this study, a data set of daily hospital admission for respiratory and cardiovascular diseases was used from the period of 1 January 2009 to 31 December 2009 (365 days).Result showed that TFPW method is an easy and useful method in removing the influence of serial correlation from the hospital admission data.It can be concluded that statistical control chart based on residual series perform better compared to original hospital admission series which influenced by the effects of serial correlation data. 2013-07-03 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/19043/1/AIPCP%20157%202014%201049-1054.pdf Mat Desa, Nor Hasliza and Jemain, Abdul Aziz (2013) Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method. In: 2013 UKM FST Post-Graduate Colloquium, 3 - 4 July 2013, Selangor, Malaysia. http://doi.org/10.1063/1.4858792 doi:10.1063/1.4858792
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Mat Desa, Nor Hasliza
Jemain, Abdul Aziz
Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method
description A key assumption in traditional statistical process control (SPC) technique is based on the requirement that observations or time series data are normally and independently distributed. The presences of a serial autocorrelation results in a number of problems, including an increase in the type I error rate and thereby increase the expected number of false alarm in the process observation.However, the independency assumption is often violated in practice due to the influence of serial correlation in the observation. Therefore, the aim of this paper is to demonstrate with the hospital admission data, the influence of serial correlation on the statistical control charts. The trend free pre-whitening (TFPW) method has been used and applied as an alternative method to obtain residuals series which are statistically uncorrelated to each other.In this study, a data set of daily hospital admission for respiratory and cardiovascular diseases was used from the period of 1 January 2009 to 31 December 2009 (365 days).Result showed that TFPW method is an easy and useful method in removing the influence of serial correlation from the hospital admission data.It can be concluded that statistical control chart based on residual series perform better compared to original hospital admission series which influenced by the effects of serial correlation data.
format Conference or Workshop Item
author Mat Desa, Nor Hasliza
Jemain, Abdul Aziz
author_facet Mat Desa, Nor Hasliza
Jemain, Abdul Aziz
author_sort Mat Desa, Nor Hasliza
title Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method
title_short Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method
title_full Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method
title_fullStr Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method
title_full_unstemmed Eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (TFPW) method
title_sort eliminating the influence of serial correlation on statistical process control charts using trend free pre-whitening (tfpw) method
publishDate 2013
url http://repo.uum.edu.my/19043/1/AIPCP%20157%202014%201049-1054.pdf
http://repo.uum.edu.my/19043/
http://doi.org/10.1063/1.4858792
_version_ 1644282601602547712
score 13.211869

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