DocumentCode
3561844
Title
Notice of Retraction
The residual T2 control chart of the multivariate heteroskedasticity process with trend patterns
Author
Zhang Min ; Zhang Chi ; He Zhen ; Tian ZhaoLong
Author_Institution
Sch. of Manage., Tianjin Univ., Tianjin, China
Volume
2
fYear
2010
Firstpage
457
Lastpage
461
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Statistical process control(SPC) is widely used to improve the product quality. The quality of a product can be attributed to several correlated quality characteristics, all of which need to be controlled and monitored simultaneously. Linear trends in processes are usually due to some type of process decay, such as the wearing out of a tool, where there is often heteroskedasticity. In this paper, the models of the residuals of the process with heteroskedasticity are fitted using Glejser test method which can test the increasing or decreasing heteroskedasticity of the process, which can distinguish three kinds of variables in the processes. Then, the identically independent random residuals after eliminating the linear trend and heteroskedasticity can be controlled by the multivariate T2 control chart. At the end, the axis diameter and surface roughness in the tool wear process are analyzed with the residual T2 control chart proposed.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Statistical process control(SPC) is widely used to improve the product quality. The quality of a product can be attributed to several correlated quality characteristics, all of which need to be controlled and monitored simultaneously. Linear trends in processes are usually due to some type of process decay, such as the wearing out of a tool, where there is often heteroskedasticity. In this paper, the models of the residuals of the process with heteroskedasticity are fitted using Glejser test method which can test the increasing or decreasing heteroskedasticity of the process, which can distinguish three kinds of variables in the processes. Then, the identically independent random residuals after eliminating the linear trend and heteroskedasticity can be controlled by the multivariate T2 control chart. At the end, the axis diameter and surface roughness in the tool wear process are analyzed with the residual T2 control chart proposed.
Keywords
control charts; statistical process control; surface roughness; Glejser test method; multivariate heteroskedasticity process; residual T2 control chart; statistical process control; surface roughness; Analytical models; Approximation methods; Correlation; ISO standards; Manufacturing; heteroskedasticity; multivariate control chart; tool wear process; trend pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Management Science (ICAMS), 2010 IEEE International Conference on
Print_ISBN
978-1-4244-6931-4
Type
conf
DOI
10.1109/ICAMS.2010.5552962
Filename
5552962
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