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

被引：56

作者：

Albert, S ^{[1
]}

Kinley, RD ^{[1
]}

机构：

[1] Eli Lilly & Co Ltd, Speke Operat, Liverpool L24 9LN, Merseyside, England

来源：

TRENDS IN BIOTECHNOLOGY | 2001年 / 19卷 / 02期

关键词：

D O I：

10.1016/S0167-7799(00)01528-6

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

This article describes the development of Multivariate Statistical Process Control (MSPC) procedures for monitoring batch processes and demonstrates its application with respect to industrial tylosin biosynthesis. Currently, the main fermentation phase is monitored using univariate statistical process control principles implemented within the G2 real-time expert system package. This development addresses integrating various process stages into a monitoring system and observing interactions among individual variables through the use of multivariate projection methods. The benefits of this approach will be discussed from an industrial perspective.

引用

页码：53 / 62

页数：10

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