Smart Process Operations and Control Lab

  • Groene Loper 19, Flux

    5612 AP Eindhoven

    Netherlands

  • P.O. Box 513, Department of Electrical Engineering

    5600 MB Eindhoven

    Netherlands

Organization profile

Introduction / mission

SPROC Lab focuses on challenges critical for the dynamic and flexible operation of chemical processes.

Organisational profile

We aim to provide technology that enables chemical process industry maintain its competitiveness in the face of developments such as Industry 4.0, electrification of process industry, circular economy and green transition. The consequence of these developments for process industry means

• Tightly integrated physical network,
• Wide range of feedstocks,
• Dynamic multiple energy sources and market prices
• Relevant information from big data

In order to address the needs of the process industry, SPROC Lab focuses on developing theory and methods in the area of modeling for control combining physical knowledge and process data, model alignment and maintenance, model based operation support technology such as model predictive control, real time optimization, interaction of scheduling and control. Additionally, SPROC investigates the integration of process design and control for intensified chemical systems and forced dynamic operation of heterogeneously catalyzed chemical reactions.

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2009 2019

Dynamic modeling of milk acidification for product design and process control

Porru, M., Ozkan, L., Huppertz, T. & Szymanska, E., 9 Oct 2019

Research output: Contribution to conferencePosterAcademic

Integration of Max-plus-linear scheduling and control

Dirza, R., Marquez Ruiz, A., Ozkan, L. & Mendez Blanco, C., 25 Jul 2019, In : Computer Aided Chemical Engineering. 46, p. 1279-1284 6 p.

Research output: Contribution to journalConference articleAcademicpeer-review

Scheduling
Decomposition
Processing
2 Citations (Scopus)

Modeling of reactive batch distillation columns for control

Marquez Ruiz, A., Mendez Blanco, C. S. & Ozkan, L., 2 Feb 2019, In : Computers and Chemical Engineering. 121, p. 86-98

Research output: Contribution to journalArticleAcademicpeer-review

Distillation columns
Distillation
Linear transformations
Process monitoring
Model predictive control

Activities 2018 2018

29th European Symposium on Computer Aided Process Engineering (ESCAPE 29)

Leyla Özkan (Organiser)
Aug 2018Jul 2019

Activity: Participating in or organising an event typesConferenceScientific

Student theses

Centralized and distributed identified model based predictive control for Museum Hermitage Amsterdam

Author: Chen, X., 22 Mar 2019

Supervisor: Lazar, M. (Supervisor 1), Ludlage, J. (Supervisor 2), Van den Hof, P. (Supervisor 2) & Lefeber, E. (Supervisor 2)

Student thesis: Master

LPV modelling and parameter estimation for reaction systems

Author: Prikken, D., 7 Sep 2018

Supervisor: Ozkan, L. (Supervisor 1), Mendez Blanco, C. (Supervisor 2) & Van den Hof, P. (Supervisor 2)

Student thesis: Master

Reactive scheduling of manufacturing plants using a safety driven modelling approach

Author: van Gameren, S., 22 Jun 2017

Supervisor: Saltik, B. (Supervisor 1) & Ozkan, L. (Supervisor 2)

Student thesis: Master