Combining fundamental knowledge and latent variable techniques to transfer process monitoring models between plants

Chemometrics and Intelligent Laboratory Systems

Volumn 116, Issue , 2012, Pages 67-77

  Tomba, Emanuele ^a   Facco, Pierantonio ^a   Bezzo, Fabrizio ^a   García Muñoz, Salvador ^b   Barolo, Massimiliano ^a  

^a UNIVERSITY OF PADOVA   (Italy)

^b PFIZER INC   (United States)

Author keywords

Design space; JY PLS; Model transfer; PAT; Process monitoring; Quality by design; Scale up

Indexed keywords

ALGORITHM; AMOUNT OF TYPE I ERROR; AMOUNT OF TYPE II ERROR; ANALYTICAL PARAMETERS; ARTICLE; CASE STUDY; CONTROLLED STUDY; DRUG INDUSTRY; ENERGY BALANCE; FAULT DETECTION; FUNDAMENTAL KNOWLEDGE; KNOWLEDGE; LATENT VARIABLE MODEL; MEAN TIME TO DETECTION; MODEL TRANSFER; NONBIOLOGICAL MODEL; PARTIAL LEAST SQUARES REGRESSION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; PROBABILITY; PROCESS MONITORING; QUALITY CONTROL; SCALE UP; SPRAY DRYING; WEIGHTED TEMPERATURE DIFFERENCE;

EID: 84861937707     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.04.016     Document Type: Article

References (34)

1. Nomikos P., MacGregor J.F. Monitoring batch processes using multiway principal component analysis. AICHE Journal 1994, 40:1361-1375.
2. Wold S., Kettaneh N., Fridèn H., Holmberg A. Modeling and diagnostics of batch processes and analogous kinetics experiments. Chemometrics and Intelligent Laboratory Systems 1998, 44:331-340.
3. Wise B.M., Gallagher N.B. The process chemometrics approach to process monitoring and fault detection. Journal of Process Control 1996, 6:329-348.
4. MacGregor J.F., Kourti T. Statistical process control of multivariate processes. Control Engineering Practice 1995, 3:403-414.
5. Feudale R.N., Woody N.A., Tan H., Myles A.J., Brown S.D., Ferré J. Transfer of multivariate calibration models: a review. Chemometrics and Intelligent Laboratory Systems 2002, 64:181-192.
6. Lu J., Gao F. Process modeling based on process similarity. Industrial and Engineering Chemistry Research 2008, 47:1967-1974.
7. Lu J., Yao K., Gao F. Process similarity and developing new process models through migration. AICHE Journal 2009, 55:2318-2328.
8. Jaeckle C.M., MacGregor J.F. Product transfer between plants using historical process data. AICHE Journal 2000, 46:1989-1997.
9. Jaeckle C.M., MacGregor J.F. Industrial applications of product design through the inversion of latent variable models. Chemometrics and Intelligent Laboratory Systems 2000, 50:199-210.
10. García-Muñoz S., MacGregor J.F., Kourti T. Product transfer between sites using Joint-Y PLS. Chemometrics and Intelligent Laboratory Systems 2005, 79:101-114.
11. Liu Z., Bruwer M.J., MacGregor J.F., Rathore S.S.S., Reed D.E., Champagne M.J. Scale-up of a pharmaceutical roller compaction process using a joint-Y partial least squares model. Industrial and Engineering Chemistry Research 2011, 50:10696-10706.
12. García-Muñoz S. Establishing multivariate specifications for incoming materials using data coming from multiple scales. Chemometrics and Intelligent Laboratory Systems 2009, 98:51-57.
13. Facco P., Tomba E., Bezzo F., García-Muñoz S., Barolo M. Transfer of process monitoring models between different plants using latent variable techniques. Ind. Eng. Chem. Res. 2012, 10.1021/ie202974u.
14. van Lith P.F., Betlem B.H.L., Roffel B. Combining prior knowledge with data driven modeling of a batch distillation column including start-up. Computers & Chemical Engineering 2003, 27:1021-1030.
15. Nandi S., Badhe Y., Lonari J., Sridevi U., Rao B.S., Tambe S.S., Kulkarni B.D. Hybrid process modeling and optimization strategies integrating neural networks/support vector regression and genetic algorithms. Study of benzene isopropylation on Hbeta catalyst. Chemical Engineering Journal 2004, 97:115-129.
16. Van sprang E.N.M., Ramaker H.-J., Westerhuis J.A., Smilde A.K., Wienke D. Statistical batch process monitoring using gray models. AICHE Journal 2005, 51:931-945.
17. Zlokarnik M. Scale Up in Chemical Engineering 2006, Wiley-VCH, Weinheim (Germany).
18. Dobry D.E., Settell D.M., Baumann J.M., Ray R.J., Graham L.J., Beyerinck R.A. A Model-based methodology for spray-drying process development. Journal of Pharmaceutical Innovation 2009, 4:133-142.
19. Graham L.J., Taillon R., Mullin J., Wigle T. Pharmaceutical process/equipment design methodology case study: cyclone design to optimize spray-dried-particle collection efficiency. Computers & Chemical Engineering 2010, 34:1041-1048.
20. García-Muñoz S., Settell D. Application of multivariate latent variable modeling to pilot-scale spray drying monitoring and fault detection: monitoring with fundamental knowledge. Computers & Chemical Engineering 2009, 33:2106-2110.
21. Food and Drug Administration, Guidance for industry PAT - A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance 2004, Office of training and communication, Division of Drug Information, HFD-240, Center for Drug Evaluation and Research, FDA, Rockville, MD (USA).
22. Jackson J.E. A User's Guide to Principal Components 1991, John Wiley & Sons, Inc., New York (U.S.A.).
23. Mardia K.V., Kent J.T., Bibby J.M. Multivariate Analysis 1979, Academic Press Limited, London (U.K.).
24. Martens H., Naes T. Multivariate Calibration 1989, John Wiley & Sons, Inc., New York (U.S.A.).
25. Fujiwara K., Kano M., Hasebe S. Development of correlation-based clustering method and its application to software sensing. Chemometrics and Intelligent Laboratory Systems 2010, 101:130-138.
26. Fujiwara K., Kano M., Hasebe S. Correlation-based spectral clustering for flexible process monitoring. Journal of Process Control 2011, 21:1438-1448.
27. Facco P., Bezzo F., Barolo M. Nearest-Neighbor method for the automatic maintenance of multivariate statistical soft sensors in batch processing. Industrial and Engineering Chemistry Research 2010, 49:2336-2347.
28. Rännar S., MacGregor J.F., Wold S. Adaptive batch monitoring using hierarchical PCA. Chemometrics and Intelligent Laboratory Systems 1998, 41:73-81.
29. Qin S.J. Recursive PLS algorithms for adaptive data modeling. Computers & Chemical Engineering 1998, 22:503-514.
30. Li W., Yue H.H., Valle-Cervantes S., Qin S.J. Recursive PCA for adaptive process monitoring. Journal of Process Control 2000, 10:471-486.
31. Cheng C., Chiu M.S. Nonlinear process monitoring using JITL-PCA. Chemometrics and Intelligent Laboratory Systems 2005, 76:1-13.
32. Montgomery D.C. Introduction to Statistical Quality Control 2005, John Wiley & Sons, Inc., New York (U.S.A.). fifth ed.
33. García-Muñoz S., Kourti T., MacGregor J.F. Model predictive monitoring for batch processes. Industrial and Engineering Chemistry Research 2004, 43:5929-5941.
34. Nomikos P., MacGregor J.F. Multivariate SPC charts for monitoring batch processes. Technometrics 1995, 37:41-59.