Improving Process Operation via Rigorous Models

Rigorous models (first principle models) are an accepted technology in process industries and development of such models are common practice.  There are various modeling environments available with complex reaction kinetics formulations and rigorous thermodynamics information. The models used have become more and more dynamic and are used for offline studies such as process design and optimization, dynamical analysis, control structure selection and operator training. These models are generally nonlinear, large scale and result in differential algebraic representations. They describe a wider range of process operation compared to data driven models. Despite their extensive offline use, the process knowledge within these rigorous models is still not utilized extensively in the production/operation environment for real time online model based applications.  The goal of this project is to integrate rigorous in daily operation of chemical processes and make a step further in closing the gap between offline and online use of rigorous models in these applications. 

We have identified two research directions in this project 

  1. Alignment of rigorous models with actual process behavior (online calibration) with a predefined level of accuracy. 
  2. Development of technology for the optimal design, dynamic operation, control and decision making for processes under uncertainty.

Partners

Case studies provided by the partners

Whey processing, FrieslandCampina
Resin production, DSM
Crystallization, CORBION

People

  • Prof. ACPM Backx
  • Prof. Paul Van den Hof
  • Prof. Siep Weiland
  • Dr. Leyla Ozkan
  • Dr. Jobert Ludlage
  • Dr. Macella Porru
  • Ir. Bahadir Saltik
  • Hernan Guidi, MSc.