Multivariate statistical analysis of an emulsion batch process

Industrial and Engineering Chemistry Research

Volumn 37, Issue 10, 1998, Pages 3971-3979

  Neogi, Debashis ^a   Schlags, Cory E ^a  

^a AIR PRODUCTS AND CHEMICALS INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR ANALYSIS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; MEASUREMENT ERRORS; STATISTICAL METHODS; VISCOSITY MEASUREMENT;

MULTIWAY PARTIAL LEAST SQUARES (MPLS) ANALYSIS; MULTIWAY PRINCIPAL COMPONENT ANALYSIS (MPCA);

EMULSION POLYMERIZATION;

EID: 0032179394     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie980243o     Document Type: Article

References (19)

1. Kourti, T.; MacGregor, J. F. Multivariate SPC Methods for Process and Product Monitoring. J. Qual. Technol. 1996, 8, 409428.
2. Nomikos, P.; MacGregor, J. F. Monitoring of Batch Processes Using Multi-way Principal Component Analysis. AIChE J. 1994, 40, 1361-1375.
3. Wold, S.; Geladi, P.; Esbensen, K.; Ohman, J. Multi-way Principal Components and PLS Analysis. J. Chemometrics 1987, 1, 41-56.
4. Nomikos, P.; MacGregor, J. F. Multivariate SPC Charts for Monitoring Batch Processes. Technometrics 1995, 37, 41-59.
5. Gallagher, N. B.; Wise, B. M.; Stewart, C. W. Application of Multi-way Principal Components Analysis to Nuclear Waste Storage Tank Monitoring. Comput. Chem. Eng. 1996, 20, S739S744.
6. Nomikos, P.; MacGregor, J. F. Multi-way Partial Least Squares in Monitoring Batch Processes. Chemo. Intell. Lab. Sys. 1995, 30, 97-108.
7. Kourti, T.; Nomikos, P.; MacGregor, J. F. Analysis, Monitoring and Fault Diagnosis of Batch Processes Using Multicblock and Multi-way PLS. J. Process Control 1995, 5, 277-284.
8. Albert, S.; Martin, E. B.; Montague, G. A.; Morris, A. J.; Multivariate Statistical Process Control in Batch Process Monitoring. 13th World IFAC Conference, San Francisco, CA, 1996.
9. Kosanovich, K. A.; Dahl, K. S.; Piovoso, M. J. Improved Process Understanding Using Multiway Principal Component Analysis. Ind. Eng. Chem. Res. 1996, 35, 138-146.
10. Dong, D.; McAvoy, T. J. Batch Tracking via Nonlinear Principal Component Analysis. AIChE J. 1996, 26, 2199-2208.
11. Kourti, T.; Lee, J.; MacGregor, J. F. Experiences with Industrial Applications of Projection Methods for Multivariate Statistical Process Control. Comput. Chem. Eng. 1996, 20, S745S750.
12. Neogi, D.; Schlags, C. E. Application of Multivariate Statistical Techniques for Monitoring Emulsion Batch Processes. Proc. Am. Control Conf. 1997, 2, 1177-1181.
13. Jackson, J. E. A User's Guide to Principal Components; Wiley-Interscience: New York, 1991.
14. Kaspar, M. H.; Ray, W. H. Dynamic PLS Modeling for Process Control. Chem. Eng. Sci. 1993, 48, 3447-3461.
15. Wold, S. Cross-Validatory Estimation of Number of Components in Factor and Principal Component Models. Technometrics 1978, 20, 397-405.
16. Lorber, A.; Wangen, L.; Kowalski, B. A Theoretical Foundation for the PLS Algorithm. J. Chemometrics 1987, 1, 19-31.
17. Geladi, P.; Kowalski, B. Partial Least Squares Regression: A Tutorial. Anal. Chim. Acta 1986, 185, 1-17.
18. Hoskuldsson, A. PLS Regression Methods. J. Chemometrics 1988, 2, 211-228.
19. Kresta, J.; MacGregor, J. F.; Marlin, T. E. Multivariate Statistical Monitoring of Process Operating Performances. Can. J. Chem. Eng. 1991, 69, 35-47.