Making use of process tomography data for multivariate statistical process control

Bundit Boonkhao, Rui F. Li, Lande Liu, Xue Z. Wang, Richard J. Tweedie, Ken Primrose, Jason Corbett, Fraser K. McNeil-Watson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a novel strategy for making effective use of on-line process tomography measurements for process monitoring. The electrical resistance tomography (ERT) sensing system equipped with sixteen electrodes provides 104 conductivity measurements every 25 milliseconds. The data has traditionally been used for construction of images for display purpose. In this study, ERT data was used for multivariate statistical process control (MSPC). Data at pre-defined normal operational conditions was processed using principal component analysis. The compressed data was used to derive two statistics; Hotelling’s T2 and squared prediction error (SPE). The Hotelling’s T2 and SPE charts predict the probability that the process being monitored has undergone statistically significant changes from previous state or the so-called normal operational state, in terms of mixing quality. The methodology is illustrated by reference to a case study of a sunflower oil/water emulsion process. © 2010, International Society for Industrial Process Tomography.
LanguageEnglish
Title of host publication6th World Congress in Industrial Process Tomography Proceeding
PublisherInternational Society for Industrial Process Tomography
Pages488-499
Number of pages12
ISBN (Print)9780853163220
Publication statusPublished - 2014
Externally publishedYes
Event6th World Congress on Industrial Process Tomography - Beijing, China
Duration: 6 Sep 20109 Sep 2010
https://www.isipt.org/world-congress/6.html

Conference

Conference6th World Congress on Industrial Process Tomography
CountryChina
CityBeijing
Period6/09/109/09/10
Internet address

Fingerprint

Statistical process control
Tomography
Acoustic impedance
Sunflower oil
Process monitoring
Principal component analysis
Emulsions
Display devices
Statistics
Electrodes
Water

Cite this

Boonkhao, B., Li, R. F., Liu, L., Wang, X. Z., Tweedie, R. J., Primrose, K., ... McNeil-Watson, F. K. (2014). Making use of process tomography data for multivariate statistical process control. In 6th World Congress in Industrial Process Tomography Proceeding (pp. 488-499). [108859] International Society for Industrial Process Tomography.
Boonkhao, Bundit ; Li, Rui F. ; Liu, Lande ; Wang, Xue Z. ; Tweedie, Richard J. ; Primrose, Ken ; Corbett, Jason ; McNeil-Watson, Fraser K. / Making use of process tomography data for multivariate statistical process control. 6th World Congress in Industrial Process Tomography Proceeding. International Society for Industrial Process Tomography, 2014. pp. 488-499
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Boonkhao, B, Li, RF, Liu, L, Wang, XZ, Tweedie, RJ, Primrose, K, Corbett, J & McNeil-Watson, FK 2014, Making use of process tomography data for multivariate statistical process control. in 6th World Congress in Industrial Process Tomography Proceeding., 108859, International Society for Industrial Process Tomography, pp. 488-499, 6th World Congress on Industrial Process Tomography, Beijing, China, 6/09/10.

Making use of process tomography data for multivariate statistical process control. / Boonkhao, Bundit; Li, Rui F.; Liu, Lande; Wang, Xue Z.; Tweedie, Richard J.; Primrose, Ken; Corbett, Jason; McNeil-Watson, Fraser K.

6th World Congress in Industrial Process Tomography Proceeding. International Society for Industrial Process Tomography, 2014. p. 488-499 108859.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Corbett, Jason

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AB - This paper describes a novel strategy for making effective use of on-line process tomography measurements for process monitoring. The electrical resistance tomography (ERT) sensing system equipped with sixteen electrodes provides 104 conductivity measurements every 25 milliseconds. The data has traditionally been used for construction of images for display purpose. In this study, ERT data was used for multivariate statistical process control (MSPC). Data at pre-defined normal operational conditions was processed using principal component analysis. The compressed data was used to derive two statistics; Hotelling’s T2 and squared prediction error (SPE). The Hotelling’s T2 and SPE charts predict the probability that the process being monitored has undergone statistically significant changes from previous state or the so-called normal operational state, in terms of mixing quality. The methodology is illustrated by reference to a case study of a sunflower oil/water emulsion process. © 2010, International Society for Industrial Process Tomography.

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Boonkhao B, Li RF, Liu L, Wang XZ, Tweedie RJ, Primrose K et al. Making use of process tomography data for multivariate statistical process control. In 6th World Congress in Industrial Process Tomography Proceeding. International Society for Industrial Process Tomography. 2014. p. 488-499. 108859