Process Performance Optimization

Please refer to the LSF​​​​​​​ for the most recent information.

The course gives an overview of state-of-the-art techniques and of their applications to evaluate and to optimize the performance of chemical and biochemical production processes. The following topics are dealt with:

• Selection of controllers and control structures

• Optimization of the operating conditions by linear programming and nonlinear optimization

• Model predictive control

• Batch trajectory optimization

• Model-based estimation of process variables for monitoring and control (state estimation)

• Process performance monitoring

• Dynamic simulation and operator training systems

• Manufacturing Execution Systems

• Statistical Process Control, Six SigmaOperation of regulated life science processes

Lab experiment:

The methods from the lecture are experimentally investigated in laboratory set-ups and computer experiments.

The students acquire an in-depth knowledge of methods and technologies for the monitoring and for the im- provement of chemical and biochemical production processes by suitable instrumentation, advanced control, model-based optimization, data analysis and continuous improvement processes. They are able to map the requirements for the safe and efficient operation of standard units (reactors, distillation columns) into suitable P&I instrumentation diagrams. They understand the different forms of optimization problems that occur in the process industry and the related solution methods. They can map the process requirements and constraints into mathematical optimization problems. The students understand the basic principles of model-predictive control and of linear and nonlinear state estimation and can set up estimators for simple problems.