Multivariate statistical monitoring of batch processes: An industrial case study of fermentation supervision

Trends in Biotechnology

Volumn 19, Issue 2, 2001, Pages 53-62

  Albert, Sarolta ^a   Kinley, Robert D ^a  

^a ELI LILLY AND COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TYLOSIN;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BACTERIUM CULTURE; DATA ANALYSIS; EXPERT SYSTEM; FERMENTATION; MONITORING; MULTIVARIATE ANALYSIS; PRIORITY JOURNAL; QUALITY CONTROL; STATISTICAL ANALYSIS;

FERMENTATION; MULTIVARIATE ANALYSIS;

BACTERIA (MICROORGANISMS);

EID: 0035253422     PISSN: 01677799     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-7799(00)01528-6     Document Type: Review

References (16)

1. Issues in industrial advisory system development
2. A theoretical basis for the use of principal components models for monitoring multivariate processes
3. Neural networks and bias/variance dilemma
4. Monitoring batch processes using multiway principal component analysis
5. Multivariate SPC charts for monitoring batch processes
6. Non-parametric confidence bounds for process performance monitoring charts
7. Artificial neural networks: Studies in process modelling and control
8. Variable selection in wavelet regression models
9. Probabilistic data based modelling: A new technique for data analysis and process modelling
10. Quality analysis with self organising neural networks