Computer-aided optimization of complex processes in production systems and urban environments

Research output: ThesisDoctoral Thesis (compilation)


Complex processes can be seen as a series of actions, changes, and/or events that are related in different temporospatial manners, and thus are potentially difficult to understand. Optimizing such a process is therefore not necessarily a simple feat, and doing it experimentally may become both time-consuming and expensive. Computer-aided optimization therefore lends itself as a viable alternative, since it can be performed in a relatively short time at a low cost, whilst providing insights into how to improve a process.

The work collected and presented in this thesis concerns three different complex processes in the two categories of production systems, and urban environments, all in need of improvements. These three cases have thus been the subjects of a series of studies collected and presented in this thesis, appended as Papers I-IX. For production systems, two cases are presented. The first case is the purification of a polyalcohol at Perstorp AB, the process of which was subject to process-disturbing oscillations that were analyzed and their effects quantified through an in-silico sensitivity analysis, and subsequently reduced by 99.7% via a computer-aided dynamic optimization approach. Secondly, the chromatographic purification of pharmaceuticals has been studied, where optimization techniques were used for the dynamic optimization of the loading phase of a capture step as well as the optimal design of integrated column sequences. In the category of urban environments, blue-green systems for urban flooding mitigation in the city of Malmö have been studied, where a model was developed and then applied for optimal economic siting and sizing of retrofits taking into account implementation and flooding-induced costs. With a 3% decrease in costs, whilst modest, this result shows that the blue-green systems are economical alternatives to consider for mitigating urban flooding.

The purpose of this thesis – in addition to improving the three aforementioned processes – is to provide tools, in the form of a procedure and a framework, that can be used to increase the accessibility of computer-aided optimization. The aim is that these tools can be useful to practitioners and facilitate studies, which in turn can be used as a foundation for improving any given complex situation or process. In addition, a summary is presented of the most important parts of an optimization problem and its formulation, and the most relevant optimization approaches to the work presented in this thesis are also summarized and explained. Furthermore, the presented tools are used to describe and analyze the work that has been performed and is presented in this thesis. They are also used to explain how the choices that are made regarding tools for modeling, simulation, and optimization may impact each other, and thus have an interplay. With these
general and generalizable tools, the aim is to contribute towards an increased understanding and thereby accessibility of computer-aided optimization.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Chemical Process Engineering


  • Optimization, modeling, simulation, complex processes, process systems engineering, preparative chromatography, blue-green systems
Original languageEnglish
Awarding Institution
Supervisors/Assistant supervisor
Thesis sponsors
  • Swedish Government Agency for Innovation Systems (Vinnova)
Award date2020 May 8
Place of PublicationLund
  • Department of Chemical Engineering, Lund University
Print ISBNs978-91-7422-732-1
Electronic ISBNs978-91-7422-733-8
Publication statusPublished - 2020 Apr 14
Publication categoryResearch

Bibliographic note

Defence details Date: 2020-05-08 Time: 9:15 Place: Lecture hall KC:A, Kemicentrum, Naturvetarvägen 14, Faculty of Engineering LTH, Lund University, Lund. Follow online: External reviewer(s) Name: Bogle, David Title: Prof. Affiliation: University College London, United Kingdom. ---

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