On The Development of Control Systems Technology for Fermentation Processes

  • John Loftus

Student thesis: Phd


Fermentation processes play an integral role in the manufacture of pharmaceutical products. The Quality by Design initiative, combined with Process Analytical Technologies, aims to facilitate the consistent production of high quality products in the most efficient and economical way. The ability to estimate and control product quality from these processes is essential in achieving this aim. Large historical datasets are commonplace in the pharmaceutical industry and multivariate methods based on PCA and PLS have been successfully used in a wide range of applications to extract useful information from such datasets. This thesis has focused on the development and application of novel multivariate methods to the estimation and control of product quality from a number of processes. The document is divided into four main categories. Firstly, the related literature and inherent mathematical techniques are summarised. Following this, the three main technical areas of work are presented. The first of these relates to the development of a novel method for estimating the quality of products from a proprietary process using PCA. The ability to estimate product quality is useful for identifying production steps that are potentially problematic and also increases process efficiency by ensuring that any defective products are detected before they undergo any further processing. The proposed method is simple and robust and has been applied to two separate case studies, the results of which demonstrate the efficacy of the technique. The second area of work concentrates on the development of a novel method of identifying the operational phases of batch fermentation processes and is based on PCA and associated statistics. Knowledge of the operational phases of a process can be beneficial from a monitoring and control perspective and allows a process to be divided into phases that can be approximated by a linear model. The devised methodology is applied to two separate fermentation processes and results show the capability of the proposed method. The third area of work focuses on undertaking a performance evaluation of two multivariate algorithms, PLS and EPLS, in controlling the end-point product yield of fermentation processes. Control of end-point product quality is of crucial importance in many manufacturing industries, such as the pharmaceutical industry. Developing a controller based on historical and identification process data is attractive due to the simplicity of modelling and the increasing availability of process data. The methodology is applied to two case studies and performance evaluated. From both a prediction and control perspective, it is seen that EPLS outperforms PLS, which is important if modelling data is limited.
Date of Award1 Aug 2017
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorBarry Lennox (Supervisor) & Joaquin Carrasco Gomez (Supervisor)


  • Principal Component Analysis
  • Partial-Least Squares
  • End-Point Control
  • Process Control
  • Multivariate Statistics
  • Product Quality

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