title: Multivariate statistical monitoring of batch processes: an industrial case study of fermentation supervision.
abstract: 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.
authors.affiliation: Eli Lilly and Company Limited, Speke Operations, Fleming Road, L24 9LN, Liverpool, UK. albert_sarolta@lilly.com
authors.forename: S
authors.initials: S
authors.lastname: Albert
authors.forename: R D
authors.initials: RD
authors.lastname: Kinley
mesh_terms: D005285:Fermentation; D015999:Multivariate Analysis