Statistical Monitoring of Multistage, Multiphase Batch Processes

IEEE Control Systems

Volumn 22, Issue 5, 2002, Pages 40-52

  Undey, Cenk ^a   Cinar, Ali ^a  

^a ILLINOIS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DRUG PRODUCTS; PRINCIPAL COMPONENT ANALYSIS; PRODUCT DEVELOPMENT; QUALITY CONTROL; STATISTICAL PROCESS CONTROL; VECTORS;

MULTIPHASE BATCH PROCESSES; STATISTICAL MONITORING;

BATCH DATA PROCESSING;

EID: 0036805179     PISSN: 1066033X     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCS.2002.1035216     Document Type: Article

References (47)

1. K.A. Kosanovich, K.S. Dahl, and M.J. Piovoso, “Improved process understanding using multiway principal component analysis,” Ind. Eng. Chem. Res., vol. 35, pp. 138-146, 1996.
2. C. Ündey, E. Tatara, B.A. Williams, G. Birol, and A. çinar, “A hybrid supervisory knowledge-based system for monitoring penicillin fermentation,” in Proc. Amer. Contr. Conf., Chicago, IL, 2000, pp. 3944-3948.
3. B.M. Wise, N.B. Gallagher, S.W. Butler, D. White, and G.G. Barna, “Acomparison of principal components analysis, multi-way principal components analysis, tri-linear decomposition and parallel factor analysis for fault detection in a semiconductor etch process,” J. Chemomet., vol. 13, pp. 379-396, 1999.
4. J.A. Westerhuis and P.M.J. Coenegracht, “Multivariate modelling of the pharmaceutical two-step process of wet granulation and tableting with multiblock partial least squares,” J. Chemomet., vol. 11, pp. 379-392, 1997.
5. C. Ündey, I. Boz, E. Oztemel, and A. çinar, “Statistical monitoring of multistage batch processes,” in Proc. AIChE Ann. Meet., Dallas, TX, 1999.
6. B.M. Wise and N.B. Gallagher, “The process chemometrics approach to process monitoring and fault detection,” J. Process Contr., vol. 6, no. 6, pp. 329-348, 1996.
7. J.V. Kresta, J.F. MacGregor, and T.E. Marlin, “Multivariate statistical monitoring of process operating performance,” Canad. J. Chem. Eng., vol. 69, pp. 35-47, 1991.
8. L.E. Wangen and B.R. Kowalski, “A multiblock partial least squares algorithm for investigating complex chemical systems,” J. Chemomet., vol. 3, pp. 3-20, 1988.
9. J.F. MacGregor, C. Jaeckle, C. Kiparissides, and M. Koutoudi, “Process monitoring and diagnosis by multiblock PLS methods,” AIChE J., vol. 40, no. 5, pp. 826-838, 1994.
10. T. Kourti, P. Nomikos, and J.F. MacGregor, “Analysis, monitoring and fault diagnosis of batch processes using multiblock and multiway PLS,” J. Process Contr., vol. 5, no. 4, pp. 277-284, 1995.
11. S. Wold, N. Kettaneh-Wold, and K. Tjessem, “Hierarchical multiblock PLS and PC models, for easier model interpretation, and as an alternative to variable selection,” J. Chemomet., vol. 10, pp. 463-482, 1996.
12. J.A. Westerhuis, T. Kourti, and J.F. MacGregor, “Analysis of multiblock and hierarchical PCA and PLS models,” J. Chemomet., vol. 12, pp. 301-321, 1998.
13. R. Boque and A.K. Smilde, “Monitoring and diagnosing batch processes with multiway regression models,” AIChE J., vol. 45, pp. 1504-1520, 1999.
14. A.K. Smilde, J.A. Westerhuis, and R. Boque, “Multiway multiblock component and covariates regression models,” J. Chemomet., vol. 14, pp. 301-331, 2000.
15. D. Dong and T.J. McAvoy, “Batch tracking via nonlinear principal component analysis,” AIChE J., vol. 42, pp. 2199-2208, 1996.
16. T. Kourti, J. Lee, and J.F. MacGregor, “Experiences with industrial applications of projection methods for multivariate statistical process control,” Comp. Chem. Eng., vol. 20, Suppl. A, p. 745, 1996.
17. S.G. Rothwell, E.B. Martin, and A.J. Morris, “Comparison of methods for handling unequal length batches,” in Proc. IFAC DYCOPS5, Corfu, Greece, 1998, pp. 66-71.
18. D. Neogi and C. Schlags, “Multivariate statistical analysis of an emulsion batch process,” Ind. Eng. Chem. Res., vol. 37, no. 10, pp. 3971-3979, 1998.
19. A. Kassidas, J.F. MacGregor, and P.A. Taylor, “Synchronization of batch trajectories using dynamic time warping,” AIChE J., vol. 44, no. 4, pp. 864-875, 1998.
20. H. Sakoe and S. Chiba, “Dynamic programming algorithm optimization for spoken word recognition,” IEEE Trans. Acoust., Speech, Signal Process., vol. 26, pp. 43-49, 1978.
21. L.R. Rabiner, A.E. Rosenberg, and S.E. Levinson, “Consideration in dynamic time warping algorithms for discrete word recognition,” IEEE Trans. Acoust., Speech, Signal Process., vol. 26, p. 575, 1978.
22. J.O. Ramsay and B.W. Silverman, Functional Data Analysis. New York: Springer-Verlag, 1997.
23. B.A. Williams and A. çinar, “An on-line monitoring and curve registration system for multivariable batch processes,” presented at AIChE Ann. Meet., Los Angeles, CA, 2000.
24. B. Williams, C. Ündey, and A. çinar, “Detection of process landmarks using registration for on-line monitoring,” in Proc. IFAC DYCOPS6, Cheju Island, Korea, 2001, pp. 257-263.
25. A.K. Smilde, “Three-way analysis. Problems and prospects,” Chemomet. Intell. Lab. Syst., vol. 15, pp. 143-157, 1992.
26. R. Bro, “PARAFAC.Tutorial and applications,” Chemomet. Intell. Lab. Syst., vol. 38, pp. 149-171, 1997.
27. J.A.Westerhuis, T. Kourti, and J.F. MacGregor, “Comparing alternative approaches for multivariate statistical analysis of batch process data,” J. Chemomet., vol.13, pp. 397-413, 1999.
28. D.J. Louwerse and A.K. Smilde, “Multivariate statistical process control of batch processes based on three-way models,” Chem. Eng. Sci., vol. 55, pp. 1225-1235, 2000.
29. K. Pearson, “On lines and planes of closest fit to systems of points in space,” Philos. Mag., vol. 2, pp. 559, 1901.
30. J.E. Jackson, A Users Guide to Principal Components. New York: Wiley, 1991.
31. R.A. Johnson and D.W. Wichern, Applied Multivariate Statistical Analysis, 4th ed. Englewood Cliffs, NJ: Prentice-Hall, 1998.
32. I.T. Jolliffe, Principal Component Analysis. New York: Springer-Verlag, 1996.
33. A. Raich and A. çinar, “Statistical process monitoring and disturbance diagnosis in multivariable continuous processes,” AIChE J., vol. 42, no. 4, pp. 995-1009, 1996.
34. S. Wold, “Cross-validatory estimation of the number of components in factor and principal components analysis,” Technomet., vol. 20, no. 4, pp. 397-405, 1978.
35. S. Wold, P. Geladi, K. Esbensen, and J. Ohman, “Multi-way principal component and PLS analysis,” J. Chemomet., vol. 1, pp. 41-56, 1987.
36. P. Nomikos and J.F. MacGregor, “Monitoring batch processes using multiway principal component analysis,” AIChE J., vol. 40, no. 8, pp. 1361-1375, 1994.
37. P. Nomikos and J.F. MacGregor, “Multivariate SPC charts for monitoring batch processes,” Technomet., vol. 37, pp. 41-59, 1995.
38. S. Wold, N. Kettaneh, H. Friden, and A. Holmberg, “Modelling and diagnostics of batch processes and analogous kinetic experiments,” Chemomet. Intell. Lab. Syst., vol. 44, pp. 331-340, 1998.
39. N.D. Tracy, J.C. Young, and R.L. Mason, “Multivariate control charts for individual observations,” J. Quality Contr., vol. 24, no. 2, pp. 88-95, 1992.
40. H. Hotelling, “Analysis of a complex of statistical variables into principal components,” J. Educ. Psychol., vol. 24, pp. 417, 1933.
41. J.E. Jackson, “Principal components and factor analysis: Part I-Principal components,” J. Quality Technol., vol. 12, no. 4, pp. 201-213, 1980.
42. G.J. Hahn and W.Q. Meeker, Statistical Intervals. A Guide to Practitioners. New York: Wiley, 1991.
43. G.E.P. Box, “Some theorems on quadratic forms applied in the study of analysis of variance problems: Effect of inequality of variance in one-way classification,” Ann. Math. Statist., vol. 25, pp. 290-302, 1954.
44. P. Miller, R.E. Swanson, and C.F. Heckler, “Contribution plots: The missing link in multivariate quality control,” Appl. Math. Comp. Sci., vol. 8, no. 4, pp. 775-792, 1998.
45. S. Rannar, J.F. MacGregor, and S. Wold, “Adaptive batch monitoring using hierarchical PCA,” Chemometr. Intell. Lab. Syst., vol. 41, pp. 73-81, 1998.
46. C. Ündey, E. Tatara, B.A. Williams, G. Birol, and A. çinar, “On-line real-time monitoring of penicillin fermentation,” in Proc. Int. Symp. Advanced Contr. Chem. Processes (ADCHEM 2000), Pisa, Italy, 2000, pp. 243-248.
47. C. Ündey, “Development of an intelligent hybrid monitoring and control system for batch processes,” Ph.D. dissertation, Univ. Istanbul, Dept. Chem. Eng., Avcilar-Istanbul, Turkey, 1999.