Combination of statistical process control (SPC) methods and classification strategies for situation assessment of batch process

Inteligencia Artificial

Volumn 10, Issue 29, 2006, Pages 99-107

  Ruiz, Magda ^a   Colomer, Joan ^a   Meléndez, Joaquim ^a  

^a UNIVERSITY OF GIRONA   (Spain)

Author keywords

Batch processes; Multiway Principal Component Analysis (MPCA); Situation assessment

Indexed keywords

EID: 33845512527     PISSN: 11373601     EISSN: 11373601     Source Type: Journal    
DOI: None     Document Type: Article

References (20)

1. J. Aguliar-Martin and R. Lopez. The process of classification and learning the meaning of linguistic descriptors of concepts. Approximate Reasoning in Decision Analysis, pages 165-175, 1982.
2. Fuat Doymaz, Jose Romagnoli, and Ahmet Palazoglu. A strategy for detection and isolation of sensor failures and process upsets. Chemometrics and Intelligent Laboratory Systems, 55:109-123, 2000.
3. Alberto Ferrer, editor. Control Estadistico Mega Variante para los Procesos del Siglo XXI. 27 Congreso Nacional do Estadistica e Investigacion Operativa (Spain), 2003.
4. Dae Sung Lee, Jong Moon Park, and Peter Vanrolleghem. Adaptive multiscale principal component analysis for on-line monitoring of a sequencing batch reactor. Journal of Biotechnology, 116:195-210, 2005.
5. Dae Sung Lee and Peter A. Vanrolleghem. Adaptive consensus principal component analysis for on-line batch process monitoring. Technical report, Fund for Scientific Reseach - Fiander (F.W.O.) and the Ghent University Resarch Fund, Coupure Links 653, B-9000 Gent, Belgium, 2003.
6. Dae Sung Lee and Peter A. Vanrolleghem. Monitoring of a sequencing batch reactor using adaptive multiblock principal component analysis. Biotechnology and Bioengineering, 82(4):489-497, mai 2003.
7. J.A. Lopes, J.C. Menezes, J.A. Westerhuis, and A.K. Smilde. Multiblock pis analysis of an industrial pharmaceutical process. Biotechnol Bioeng, (80):419-427, 2002.
8. K. Moore. Using neural nets to analyse qualitative data. A Marketing Research, 7(1):35-39, 1995.
9. Paul Nomikos and John MacGregor. Multivariatc spc charts for monitoring batch process. Technometrics, 37(1):41-59, feb 1995.
10. Paul Nomikos and John F. MacGregor. Monitoring batch processes using multiway principal component analysis. AIChE, 40(8):1361-1375, aug 1994.
11. Paul Nomikos and John F. MacGregor. Multi-way partial least squares in monitoring batch processes. First International Chemometrics InterNet Conference, 1994.
12. Aras Norvilas, Eric Tatara, Antoine Negiz, Jeffrey DeCicco, and All Cinar, editors. Monitoring and fault diagnosis of a polymerization reactor by interfacing knowledge based and multivariate SPM tools, number 0-7803-453. American Control Conference, 1998.
13. a IWA Specialised Conference on Sequencing Batch Reactor, Australia, feb 2004.
14. Evan L. Russell, Leo H. Chiang, and Richard D. Braatz. Data-driven techniques for fault detection and diagnosis in chemical processes "Advances in Industrial Control". ISBN 1-85233-258-1, London, 2000.
15. Age K. Smilde, Johan A. Westerhuis, and Ricard Boqué. Multiway multiblock component and covariates regression models. Journal of Chemometrics, 14:301-331, 2000.
16. Cenk Undey and Ali Cinar. Statistical monitoring of multistage, multiphase batch processes. IRRE Control Systems Magazine, 22(5):40-52, oct 2002.
17. Cenk Undey, Bruce A. Williams, and All Cinar, editors. Monitoring of Batch Pharmaceutical Fermentations: Data Synchronization, Landmark Alignment, and Real-Time Monitoring. 15th Triennial World Congress, Barcelona Spain 2002 IFAC, 2002.
18. V. Venkatasubramanian, R. Rengaswamy, K. Yin, and S. Kavuri. A review of process fault detection and diagnosis part i quantitative model-based methods. Computer and Chemical Engineering, 27:293-311, 2003.
19. Johan A. Westerhuis, Theodora Kourti, and John F. MacGregor. Analysis of multiblock and hierarchical pca and pis models. Journal of Chemometrics, 12:301-321, 1998.
20. Manuel Zarzo and Alberto Ferrer. Batch process diagnosis: Pis with variable selection versus block-wise per. Chemometrics and intelligent laboratory systems, 73:15-27, jun 2004.