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On-line statistical monitoring of batch processes using Gaussian mixture model

Chen, T and Zhang, J (2009) On-line statistical monitoring of batch processes using Gaussian mixture model In: 7th IFAC International Symposium on Advanced Control of Chemical Processes, 2009-07-12 - 2009-07-15, Istanbul, Turkey.

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Abstract

The statistical monitoring of batch manufacturing processes is considered. It is known that conventional monitoring approaches, e.g. principal component analysis (PCA), are not applicable when the normal operating conditions of the process cannot be sufficiently represented by a Gaussian distribution. To address this issue, Gaussian mixture model (GMM) has been proposed to estimate the probability density function of the process nominal data, with improved monitoring results having been reported for continuous processes. This paper extends the application of GMM to on-line monitoring of batch processes, and the proposed method is demonstrated through its application to a batch semiconductor etch process.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Chen, Tt.chen@surrey.ac.ukUNSPECIFIED
Zhang, JUNSPECIFIEDUNSPECIFIED
Date : 2009
Identification Number : https://doi.org/10.3182/20090712-4-TR-2008.00108
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:11
Last Modified : 17 May 2017 15:02
URI: http://epubs.surrey.ac.uk/id/eprint/834360

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