JITL based local monitoring method for transitions of multiphase batch processes

Author

Feifan Shen ; Zhihuan Song ; Zhiqiang Ge

Author_Institution

State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China

fYear

2014

fDate

4-6 June 2014

Firstpage

1957

Lastpage

1962

Abstract

Quality-relevant monitoring for multiphase batch processes is necessary. Between-phase transitions carry significant quality information and need particular attentions. In this paper, a Just-in-time-learning (JITL) based method is introduced to identify transitions and update modeling dataset of transitions. Due to the non-Gaussian distribution of the samples in the local model, a PLS-SVDD based method is proposed for modeling and monitoring. Fed-batch penicillin fermentation process is tested for performance evaluation of the proposed method.

Keywords

batch processing (industrial); fermentation; just-in-time; learning (artificial intelligence); process monitoring; production engineering computing; quality management; support vector machines; JITL based local monitoring method; PLS-SVDD based method; between-phase transitions; fed-batch penicillin fermentation process; just-in-time-learning based method; multiphase batch process transitions; nonGaussian distribution; performance evaluation; quality-relevant monitoring; support vector data description; Batch production systems; Industrial control; Laboratories; Matrix decomposition; Monitoring; Substrates; Fault detection/accommodation;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2014

Conference_Location

Portland, OR

ISSN

0743-1619

Print_ISBN

978-1-4799-3272-6

Type

conf

DOI

10.1109/ACC.2014.6858792

Filename

6858792