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978-3-8439-1904-3, Reihe Technische Chemie
Representation of Expert Knowledge on Biochemical Process Design
193 Seiten, Dissertation Technische Universität Dortmund (2014), Softcover, A5
Multicomponent mixtures with partly unknown ingredients are typical challenges in biochemical downstream process design. The behavior of these mixtures in separation processes is often not predictable with established computer-aided methods and tools due to lacking property data. Process design for biochemical products can be facilitated using heuristic knowledge derived from former experiences. However, such knowledge is distributed over many sources, provided in different forms, and often accessible by a limited number of experts only. Hence the knowledge cannot be integrated efficiently into the design process.
In this dissertation, an approach to computer-aided, knowledge-based process design is presented. The knowledge represented and methods developed assist the setup of alternative sequences of downstream operations. A generic process design workflow is described and represented in an intermediate form. This intermediate form of representation contains the knowledge required and structures the procedure needed to follow the steps of the workflow. The following process design tasks can benefit from knowledge-based assistance: (1) determination of physicochemical property data, (2) technology selection, and (3) technology evaluation.
Relevant knowledge assisting these three tasks was structured, conceptually modeled and represented using ontologies. Ontologies are extensible, easily accessible and comprehensible by humans. They are formally defined and processible by computers. They enable systematic knowledge deduction based on information contained. In this thesis, the knowledge represented in the ontologies and the problem-solving process are described. The problem-solving process is demonstrated on two exemplary processes: a model process for separating four proteins and penicillin V purification from fermentation broth.