Anlagen- und Prozesstechnik

In the course "Anlagen- und Prozesstechnik", students are taught the fundamentals of process development and plant design. Following an introduction to the process of plant design and construction, the
synthesis of conceptual flowsheets including in-process heat transfer and corresponding analytical methods will be covered. The use of statistical methods for the evaluation of experiments is also a part of the course. Based on the presentation of design fundamentals and apparatus for the handling of gases and liquids, knowledge is imparted for the installation and piping design of chemical and biotechnological plants.
Corresponding cost estimation methods and different methods of calculation will be presented, depending on the time and the level of detail of the planning of a plant. The corresponding cost estimation methods and various investment calculations are presented. Furthermore, a sub-area of quality assurance Good Manufacturing Practice (GMP), which sets out the rules for all biological and non-biological and non-biological manufacturing processes of active ingredients and medicinal products, which ensure product quality by by controlling the process and the manufacturing environment.

Students are able to work competently as a member of a team in the planning, construction and operation of chemical and biotechnological production plants and to specify process engineering tasks for specialists from other disciplines and integrate partial solutions. In particular, they understand the interplay between process engineering design and evaluation through process simulation and can contribute this knowledge to project planning teams. In addition, at each design stage in the construction of a plant, students will be able to cost-engineer the process they have designed, including all unit operations included, and perform appropriate capital budgeting. Furthermore, the students are not only able to design the plant in accordance with GMP rules, but also to evaluate it with regard to its energy efficiency and optimize it by means of in-process heat transfer. gation. You will be able to plan and evaluate necessary experiments with the help of statistical tools.