Issues in the development of an industrial bioprocess advisory system

Trends in Biotechnology

Volumn 18, Issue 4, 2000, Pages 136-141

  Glassey, Jarka ^a   Montague, Gary ^a   Mohan, Pankaj ^b  

^a NEWCASTLE UNIVERSITY   (United Kingdom)

^b Eli Lilly Speke Operations   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DISSOLVED OXYGEN;

ALGORITHM; BIOPROCESS; BIOREACTOR; EXPERT SYSTEM; FERMENTATION; INDUSTRY; INFORMATION SYSTEM; NONHUMAN; OPERATOR; PRIORITY JOURNAL; REVIEW;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOTECHNOLOGY; EXPERT SYSTEMS; FERMENTATION; MULTIVARIATE ANALYSIS; QUALITY CONTROL;

EID: 0034176692     PISSN: 01677799     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-7799(00)01423-2     Document Type: Review

References (20)

1. Karim, M.N. and Halme, A. (1988) Reconciliation of measurement data in fermentation using online expert system. In Proc. 4th Int. Congress on Computer Applications in Fermentation Technology - Modelling and Control of Biotechnical Processes (Fish, N. and Fox, R.I., eds), SCI/IFAC, pp. 37-46, Ellis Horwood
2. Fowler, G. et al. (1992) Development of real-time expert systems approach for the online analysis of fermentation respiration data. Proc. 2nd IFAC Symposium on Modelling and Control of Biotechnical Processes (173-178), Pergamon Press
3. Cooney, C.L. et al. (1988) An expert system for intelligent supervisory control of fermentation processes. In Proc of 8th Int. Biotech. Symp. (Durand, G. et al., eds), pp. 563-575, Societe francaise de microbiologie
4. Halme, A. and Visala, A. (1991) Combining symbolic and numerical information in modelling the state of biotechnological processes. In Proc. ECC, pp. 218-223, Hermes
5. Alford, J. et al. (1992) Development of real-time expert system applications for the online analysis of fermentation data. Proc. 9th Int. Biotech. Symposium and Exposition, 375-379
6. Konstantinov, K.B. et al. (1994) Expert systems in the control of animal cell culture processes: potentials, functions and perspectives. Cytotechnology 14, 233-246
7. Ross, D. et al. (1998) Predictive inferencing and graphical knowledge representation. Gensym User Symposium 1998
8. Lant, P.A. et al. (1993) On the applicability of adaptive bioprocess state estimators. Biotechnol. Bioeng. 42, 1311-1321
9. Kramer, M.A. and Fjellheim, R. (1996) Fault diagnosis and computer aided diagnostic advisors. In AICHE Symposium series 0065-8812 (Vol. 92, 312), pp. 12-24, American Institute of Chemical Engineers
10. Gregersen, L. and Jørgensen, S.B. (1999) Supervision of fed-batch ferementations. Chem. Eng. J. 75, 69-76
11. Nomikos, P. and MacGregor, J.F. (1995) Monitoring of batch processes using multi-way principal component analysis. AIChE J. 40, 1361-1375
12. Dong, D. and McAvoy, T.J. (1996) Non-linear principal component analysis based on principal curves and neural networks. Comput. Chem. Eng. 65-78
13. Glassey, J. et al. (1994) Enhanced supervision of recombinant E. coli fermentations via artificial neural networks. Process Biochem. 29, 387-398
14. Bakshi, B.R. et al. (1994) Analysis of operating data for evaluation, diagnosis and control of batch operations. J. Process Cont. 4, 179-194
15. Konstantinov, K.B. and Yoshida, T. (1992) Real-time qualitative analysis of temporal shapes of (bio)process variables. AIChE J. 38, 1703-1715
16. Cheung, J.T.Y. and Stephanopoulos, G. (1990) Representation of process trends - Part I. A formal representation framework. Comp. Chem. Engng. 495-510
17. Whiteley, J.R. and Davis, J.F. (1993) Qualitative interpretation of sensor patterns, IEEE Expert, 54-63
18. Alford, J. et al. (1999) Real rewards from artificial intelligence. In Tech, ISA, 52-55
19. Calam, C.T. (1976) Starting investigational and production cultures. Proc. Biochem. 11, 7-12
20. Warr, S.R.C. et al. (1996) Seed stage development for improved fermentation performance: increased milbemycin production by Streptomyces hygroscopicus. J. Ind. Microbiol. 16, 295-300