期刊
JOURNAL OF PHARMACEUTICAL SCIENCES
卷 108, 期 1, 页码 439-450出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.xphs.2018.07.033
关键词
multivariate statistical process monitoring; principal component analysis; in-process monitoring; continuous manufacturing
资金
- FCT (Fundacao para a Ciencia e Tecnologia)
- POPH (Programa Operacional Potencial Humano) [SFRH/BPD/74788/2010]
- European Union [POCI/01/0145/FEDER/007265]
- National Fund (FCT/MEC, Fundacao para a Ciencia e Tecnologia) [PT2020 UDI/QUI/50006/2013]
- National Fund (FCT/MEC, Ministerio da Educacao e Ciencia) [PT2020 UDI/QUI/50006/2013]
The present work presents an in-depth evaluation of continuously collected data during a twin-screw granulation and drying process performed on a continuous manufacturing line. During operation, the continuous line logs 49 univariate process variables, hence generating a large amount of data. Three identical 5-h continuous manufacturing runs were performed. Multivariate data analysis tools, more specifically latent variable modeling tools such as principal component analysis, were used to extract information from the generated data sets unveiling process trends and drifts. Furthermore, a statistical process monitoring strategy is presented. The approach is based on the application of multivariate statistical process monitoring to model the variables that remain around a steady state. (C) 2019 Published by Elsevier Inc. on behalf of the American Pharmacists Association.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据