Multivariate SPC for Non-Normal Equipment Variables and Its Applications Plasma Etchers
Date Issued
2004
Date
2004
Author(s)
Wang, Hui-Qing
DOI
en-US
Abstract
T2 control charts have been implemented in many multivariate statistical process control (MSPC) solutions. However, there are still problems hindering the implementation and the effective use of T2 control charts for equipment fault detection and classification (FDC). An important problem is that most equipment variables violate the normality assumption behind the T2 statistic. Even worse is that those non-normal variables are also correlated with one another and cause infeasibility of traditional T2 control charts. The objective of this paper is to propose a systematic multivariate FDC methodology for non-normal equipment variables.
We propose two types of methodologies, namely, normal transformation method and variance adjustment method, to remedy for the normal violation in constructing the multivariate control charts. We first introduce the methodologies without considering correlation among variables, and then present methodologies with consideration of the multivariate structure. And we will show the method of fault classification of each T2 control chart constructing methodology. Then, the comparison of all methodologies will be given.
The proposed methodologies are applied to detection and classification faults for a particular tool function of a plasma etcher in semiconductor fabrication.
Subjects
多變數製程管制
非常態參數
Multivariate SPC
Non-normal variables
Type
thesis
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