Sirkka-Liisa Jämsä-Jounela
Department of Chemical and Metallurgical Engineering

Sirkka-Liisa Jämsä-Jounela

Contact information

Full researcher profile
https://research.aalto.fi/...

Description

Professor in Process Control & Automation, Vice-Dean (Research)

My research focuses on megatrends in the field of process automation: industry 4.0, Industrial Internet of Things, Cloud Computing, Big Data, 5G, AI and their applications in the different fields of process industries. I am also interested in developing new process control and management theories, in order to run factories more efficiently and sustainably.

For process control we focus on are Model Predictive Control (MPC), and in data analytics we develop our own Fault Detection & Diagnosis (FDD) algorithms based on the problem under study. Algorithms are tested by simluation, but we have a particular focus on proof of concept in industry, together with European key research groups in the field

In addition to this research work, I am actively involved in the Academy of Finland, Research Council of Natural Sciences and Engineering, and also a member of the Aalto Research & Innovation steering group as a representative of the School of Chemical Engineering.

Research Group: Process Control and Automation

List of publications and other research outputs: Aalto Research portal

Elsewhere:

Honors and awards

Award or honor granted for a specific work
Department of Biotechnology and Chemical Technology
Jan 2013

Kultainen ansiomerkki Suomen Automaatioseura, Finland

Award or honor granted for a specific work
Department of Biotechnology and Chemical Technology
Jan 2002

The Control Engineering Practice Paper Prize IFAC (International Federation of Automatic Control), Austria

Award or honor granted for a specific work
Department of Chemical and Metallurgical Engineering
Dec 2016

SVR R I <br/>SVR R I Knight<br/>

Award or honor granted for a specific work
Department of Chemical and Metallurgical Engineering
Jul 2008

IFAC outstanding service award for sustained outstanding performance in major leadership postitions in IFAC

Publications

Department of Chemical and Metallurgical Engineering, Process Control and Automation

Industry 4.0 based process data analytics platform

Publishing year: 2020 International Journal of Electrical Power and Energy Systems
Department of Chemical and Metallurgical Engineering, Aalto University, Process Control and Automation

Optimal planning of municipal solid waste management systems in an integrated supply chain network

Publishing year: 2019 Computers and Chemical Engineering
Department of Chemical and Metallurgical Engineering, Process Control and Automation

A Multi-Echelon Supply Chain Model for Sustainable Electricity Generation from Municipal Solid Waste

Publishing year: 2019 IFAC-PapersOnLine
Process Control and Automation, Department of Chemical and Metallurgical Engineering, School services, CHEM

Control Strategy of a Multiple Hearth Furnace Enhanced by Machine Learning Algorithms

Publishing year: 2019
Process Control and Automation, Department of Chemical and Metallurgical Engineering

Hybrid causal analysis combining a nonparametric multiplicative regression causality estimator

Publishing year: 2019 Control Engineering Practice
Department of Chemical and Metallurgical Engineering, Process Control and Automation

Sustainable supply chain network design for the optimal utilization of municipal solid waste

Publishing year: 2019 AIChE Journal
Process Control and Automation, Department of Chemical and Metallurgical Engineering

Control strategy for a multiple hearth furnace in kaolin production

Publishing year: 2018 Control Engineering Practice
Process Control and Automation, Department of Chemical and Metallurgical Engineering

Simplified Mechanistic Model of the Multiple Hearth Furnace for Control Development

Publishing year: 2018 Simulation Notes Europe
Process Control and Automation, Department of Chemical and Metallurgical Engineering

Control Strategy For A Multiple Hearth Furnace

Publishing year: 2018 IFAC-PapersOnLine
Department of Chemical and Metallurgical Engineering, Process Control and Automation

Optimal control of a rougher flotation cell using adaptive dynamic programming

Publishing year: 2018 IFAC-PapersOnLine