Datenbestand vom 10. Dezember 2024
Verlag Dr. Hut GmbH Sternstr. 18 80538 München Tel: 0175 / 9263392 Mo - Fr, 9 - 12 Uhr
aktualisiert am 10. Dezember 2024
978-3-8439-3186-1, Reihe Technische Chemie
Katrin Brandt Sensitivity-based method to support early stage design of biochemical processes
217 Seiten, Dissertation Technische Universität Dortmund (2016), Softcover, A5
Decisions made in early phases of bioprocess development are to large extent responsible for the later performance and cost-efficiency of the industrial scale process. As early as possible process design should therefore follow a systematic design strategy. Thereby, experimental design approaches are typically chosen for early stages, while later on model-based design approaches are preferred. This comparatively late entry of modeling and simulation in the bioprocess design workflow does certainly not exploit the full potential of this design principle.
Therefore, a new sensitivity-based design approach is developed in this thesis, which integrates modeling and simulation in early stage process design. The basic idea is to apply the sensitivity analysis known from Design of Experiments to modeling and simulation. The resulting sensitivity ranking identifies the most significant influences of a unit operation or process under investigation, which enables experimental studies to concentrate thereon. An optimization along the resulting response surface determines the most promising process alternatives, which points the direction of future design work. As a basis for this integrated design approach the heuristic-numeric design approach is chosen.
In addition to the design strategy proposed, the separation performance indicator is derived as new key performance indicator.
Both the sensitivity-based design strategy as well as the separation performance indicator are demonstrated first in an introductory example of an adsorption-desorption step with subsequent solvent regeneration. In a second example the strategy is applied to the purification of monoclonal antibodies.