Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data

Rui F. Li; Lande Liu; Xue Z. Wang; Richard Tweedie; Ken Primrose; Jason Corbett; Fraser McNeil-Watson

doi:10.1016/S1570-7946(09)70610-8

Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

This paper describes the use of multiple on-line sensors including electrical resistance tomography (ERT), dynamic light scattering (DLS) and ultrasound spectroscopy (USS) for real-time characterization of process operations processing emulsions and nanoparticle slurries. The focus is on making novel use of the spectroscopic data to develop multivariate statistical process control (MSPC) strategies. The ERT data at different normal operating conditions was processed using principal component analysis and used to derive two MSPC statistics, T² and SPE (squared prediction error) for detecting abnormal changes in mixing conditions. The corresponding particle size distribution was monitored using DLS and USS. Two case studies, a sunflower oilwater emulsion system and a silica suspension system, were examined.

Original language	English
Title of host publication	10th International Symposium on Process Systems Engineering - PSE2009
Subtitle of host publication	Part A
Editors	Rita de Brito Alves, Claudio Oller do Nascimento, Evaristo Biscaia
Publisher	Elsevier
Pages	1317-1322
Number of pages	6
Volume	27
Edition	1
ISBN (Electronic)	9780444534422
ISBN (Print)	9780444534354
DOIs	https://doi.org/10.1016/S1570-7946(09)70610-8
Publication status	Published - 5 Aug 2009
Externally published	Yes
Event	10th International Symposium on Process Systems Engineering - Salvador-Bahia, Brazil Duration: 16 Aug 2009 → 20 Aug 2009 Conference number: 10

Publication series

Name	Computer Aided Chemical Engineering
Publisher	Elsevier
ISSN (Print)	1570-7946

Conference

Conference	10th International Symposium on Process Systems Engineering
Abbreviated title	PSE2009
Country/Territory	Brazil
City	Salvador-Bahia
Period	16/08/09 → 20/08/09

Access to Document

10.1016/S1570-7946(09)70610-8Licence: Unspecified

Cite this

Li, R. F., Liu, L., Wang, X. Z., Tweedie, R., Primrose, K., Corbett, J., & McNeil-Watson, F. (2009). Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data. In R. de Brito Alves, C. Oller do Nascimento, & E. Biscaia (Eds.), 10th International Symposium on Process Systems Engineering - PSE2009: Part A (1 ed., Vol. 27, pp. 1317-1322). (Computer Aided Chemical Engineering). Elsevier. https://doi.org/10.1016/S1570-7946(09)70610-8

Li, Rui F. ; Liu, Lande ; Wang, Xue Z. et al. / Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data. 10th International Symposium on Process Systems Engineering - PSE2009: Part A. editor / Rita de Brito Alves ; Claudio Oller do Nascimento ; Evaristo Biscaia. Vol. 27 1. ed. Elsevier, 2009. pp. 1317-1322 (Computer Aided Chemical Engineering).

@inproceedings{e9e91628b11f4cd698a7a644d2dbe3a6,

title = "Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data",

abstract = "This paper describes the use of multiple on-line sensors including electrical resistance tomography (ERT), dynamic light scattering (DLS) and ultrasound spectroscopy (USS) for real-time characterization of process operations processing emulsions and nanoparticle slurries. The focus is on making novel use of the spectroscopic data to develop multivariate statistical process control (MSPC) strategies. The ERT data at different normal operating conditions was processed using principal component analysis and used to derive two MSPC statistics, T2 and SPE (squared prediction error) for detecting abnormal changes in mixing conditions. The corresponding particle size distribution was monitored using DLS and USS. Two case studies, a sunflower oilwater emulsion system and a silica suspension system, were examined.",

keywords = "Acoustic spectroscopy, Dynamic light scattering, Multivariate statistical process control, Process tomography",

author = "Li, {Rui F.} and Lande Liu and Wang, {Xue Z.} and Richard Tweedie and Ken Primrose and Jason Corbett and Fraser McNeil-Watson",

year = "2009",

month = aug,

day = "5",

doi = "10.1016/S1570-7946(09)70610-8",

language = "English",

isbn = "9780444534354",

volume = "27",

series = "Computer Aided Chemical Engineering",

publisher = "Elsevier",

pages = "1317--1322",

editor = "{de Brito Alves}, Rita and {Oller do Nascimento}, Claudio and Evaristo Biscaia",

booktitle = "10th International Symposium on Process Systems Engineering - PSE2009",

address = "Netherlands",

edition = "1",

note = "10th International Symposium on Process Systems Engineering, PSE2009 ; Conference date: 16-08-2009 Through 20-08-2009",

}

Li, RF, Liu, L, Wang, XZ, Tweedie, R, Primrose, K, Corbett, J & McNeil-Watson, F 2009, Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data. in R de Brito Alves, C Oller do Nascimento & E Biscaia (eds), 10th International Symposium on Process Systems Engineering - PSE2009: Part A. 1 edn, vol. 27, Computer Aided Chemical Engineering, Elsevier, pp. 1317-1322, 10th International Symposium on Process Systems Engineering, Salvador-Bahia, Brazil, 16/08/09. https://doi.org/10.1016/S1570-7946(09)70610-8

Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data. / Li, Rui F.; Liu, Lande; Wang, Xue Z. et al.

10th International Symposium on Process Systems Engineering - PSE2009: Part A. ed. / Rita de Brito Alves; Claudio Oller do Nascimento; Evaristo Biscaia. Vol. 27 1. ed. Elsevier, 2009. p. 1317-1322 (Computer Aided Chemical Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data

AU - Li, Rui F.

AU - Liu, Lande

AU - Wang, Xue Z.

AU - Tweedie, Richard

AU - Primrose, Ken

AU - Corbett, Jason

AU - McNeil-Watson, Fraser

N1 - Conference code: 10

PY - 2009/8/5

Y1 - 2009/8/5

N2 - This paper describes the use of multiple on-line sensors including electrical resistance tomography (ERT), dynamic light scattering (DLS) and ultrasound spectroscopy (USS) for real-time characterization of process operations processing emulsions and nanoparticle slurries. The focus is on making novel use of the spectroscopic data to develop multivariate statistical process control (MSPC) strategies. The ERT data at different normal operating conditions was processed using principal component analysis and used to derive two MSPC statistics, T2 and SPE (squared prediction error) for detecting abnormal changes in mixing conditions. The corresponding particle size distribution was monitored using DLS and USS. Two case studies, a sunflower oilwater emulsion system and a silica suspension system, were examined.

AB - This paper describes the use of multiple on-line sensors including electrical resistance tomography (ERT), dynamic light scattering (DLS) and ultrasound spectroscopy (USS) for real-time characterization of process operations processing emulsions and nanoparticle slurries. The focus is on making novel use of the spectroscopic data to develop multivariate statistical process control (MSPC) strategies. The ERT data at different normal operating conditions was processed using principal component analysis and used to derive two MSPC statistics, T2 and SPE (squared prediction error) for detecting abnormal changes in mixing conditions. The corresponding particle size distribution was monitored using DLS and USS. Two case studies, a sunflower oilwater emulsion system and a silica suspension system, were examined.

KW - Acoustic spectroscopy

KW - Dynamic light scattering

KW - Multivariate statistical process control

KW - Process tomography

UR - http://www.scopus.com/inward/record.url?scp=77649308719&partnerID=8YFLogxK

UR - https://www.elsevier.com/books/10th-international-symposium-on-process-systems-engineering-pse2009/de-brito-alves/978-0-444-53435-4

U2 - 10.1016/S1570-7946(09)70610-8

DO - 10.1016/S1570-7946(09)70610-8

M3 - Conference contribution

AN - SCOPUS:77649308719

SN - 9780444534354

VL - 27

T3 - Computer Aided Chemical Engineering

SP - 1317

EP - 1322

BT - 10th International Symposium on Process Systems Engineering - PSE2009

A2 - de Brito Alves, Rita

A2 - Oller do Nascimento, Claudio

A2 - Biscaia, Evaristo

PB - Elsevier

T2 - 10th International Symposium on Process Systems Engineering

Y2 - 16 August 2009 through 20 August 2009

ER -

Li RF, Liu L, Wang XZ, Tweedie R, Primrose K, Corbett J et al. Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data. In de Brito Alves R, Oller do Nascimento C, Biscaia E, editors, 10th International Symposium on Process Systems Engineering - PSE2009: Part A. 1 ed. Vol. 27. Elsevier. 2009. p. 1317-1322. (Computer Aided Chemical Engineering). doi: 10.1016/S1570-7946(09)70610-8

Multivariate Statistical Control of Emulsion and Nanoparticle Slurry Processes Based on Process Tomography, Dynamic Light Scattering, and Acoustic Sensor Data

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this