Control Engineering Laboratory - University of Oulu methods and applications and COST E36 action on...

ANNUAL REPORT 2007

UNIVERSITY of OULUOULUN YLIOPISTO

1958 2008

Control Engineering Laboratory

Department of Process andEnvironmental Engineering

University of OuluOulu, Finland

Edited by

Leena Yliniemi

Control Engineering Laboratory

Department of Process and

EnvironmentalEngineering

University of OuluOulu, Finland

ANNUAL REPORT

2007

UNIVERSITY of OULUOULUN YLIOPISTO

1958 2008

PREFACE

The national project taking care of the responsibility of the European ESNA project, concerned with wireless sensor networks, began in 2007. Earlier projects continued: NiSIS (Nature Inspired Smart Information Systems) concentrating on large areas of nature inspired methods and applications and COST E36 action on Modelling and Simulation in the Pulp and Paper Industry. A small NiSIS Task Force on Immune Inspired Systems was also carried out.

Research projects developed in new areas: two co-operative projects, where the laborato-ry’s contribution was on simulation technologies, started; one in the utilization of CO2 and one in bioethanol reforming. A totally new area was confronted also in a co-operation project dealing with intelligent analysis of Barkhausen noise measurement. Also a new project in biological water treatment area was started. Two projects ended: ReGenGas-project which demonstrated, at a laboratory scale, the new process combining reforming and direct reduction processes and also Stokeri-project concerned with the modelling and control of burning in small-scale stoker fired boilers. It however will continue as ERA-NET Bioenergy project called COPECOM. Production 2010 continued under the new name, ProductionPro. Two industrial projects, one with Rautaruukki (modelling of the vacuum process), and one with Kemira on wastewater control continued.

Two new doctors finished their studies during 2007: Jarmo Keski-Säntti and Jari Näsi. The laboratory participated also in two Graduate Schools financed by the Finnish Academy: International Ph.D. Programme in Pulp and Paper Science and Technology and Graduate School in Chemical Engineering.

Student exchange with University of Loughborough (UK), University of Leuven (Belgium), and IFMA (France) continued as usual.

I would like to thank all our colleagues, friends, companies and institutions in Finland and abroad for their valuable contributions to the success of our activities.

Kauko LeiviskäProfessor

ANNUAL REPORT 2007�

CONTENTS

Page

PREFACE 3

1 PERSONNEL 6

2 EDUCATIONAL ACTIVITIES 8

2.1 University Courses 8

2.2 ERASMUS Exchange Student Programme 11

3 RESEARCH 12

3.1 International Projects 12

3.1.1 COST E36: Modelling and Simulation in the Pulp and Paper Industry 12

3.1.2 Nature-Inspired Smart Information Systems (NiSIS) 12

3.1.3 Immune System Inspired Health Monitoring of Machinery using the Danger Theory 12

3.1.4 European Sensor Network Architecture (ESNA 13

3.1.5 Exchange Student Projects 13

3.2 Research Projects 14

3.2.1 Implementing Intelligent Systems on Multiparameter Barkhausen Noise Measurements (INTELBARK) 14

3.2.2 Towards Utilization of CO2 as a Green and Versatile Commodity Chemical: Clean Synthesis of Methanol and Dimethyl Carbonate (CO2UTIL) 14

3.2.3 Control Potential of Different Operating Methods in Small-scale Wood Pellet Combustion (COPECOM) 15

3.2.4 Hydrogen Production for Fuel Cells by Bioethanol Reforming 15

3.2.5 Control and Optimisation in Biological Water Treatment (BioConOpti) 16

3.2.6 TuotantoPro/Tuotanto2010: Operational Decision Making in the Process Industry (Multidisciplinary approach) 16

3.2.7 ReGenGas - Hybrid Reforming Process for the Recycling of Greenhouse Gases and for Upgrading in the Reduction and Combustion processes 17

�ANNUAL REPORT 2007

Page

3.2.8 MATTA- On-line Quality Control as a Tool for Quality Assurance and Production Management 17

3.2.9 Production of Demanding Steel Products by Advanced Ladle Metallurgy and Casting (VAATIVA) 18

3.2.10 STOKERI- Advanced Control of Small-scale Stoker Fired Boilers 2 18

3.3 Industrial Projects 19

3.3.1 KemOpti - Optimisation and Automatic Tuning Methods for Kemira Dosage Tools 19

3.4 Other Projects 19

3.4.1 Intelligent Dynamic Simulation with Uncertainty 19

3.4.2 Intelligent Condition Monitoring 20

3.5 Doctoral Thesis Projects 21

3.5.1 Process Analysis and Management of Wood Handling Plant 21

3.5.2 Integration of Intelligent Systems in Development of Smart Adaptive Systems 21

3.5.3 Modelling for Management of LD-KG-converter 21

3.5. 4 Measurement and Control Methods for Small-Scale Biomass Combustion 22

� THESIS 23

Degree for Diploma Engineer 23

Degree for Doctor of Technology 24

� PARTICIPATIONS 26

6 PAPERS AND PUBLICATIONS 28

7 VISITS 30

8 OTHERS 31

ANNUAL REPORT 20076

1. PERSONNEL

HEADLEIVISKÄ Kauko D.Sc. (Tech.), Professor

CHIEF ENgINEERYLINIEMI Leena D.Sc. (Tech.), Docent

SENIOR ASSISTANTS JAAKO Juha D.Sc. (Tech.), on leave working as a Research Coordinator in the Research Assessment Exercise 2007

JUUSO Esko M.Sc. (Tech.)

ASSISTANTSOHENOJA Markku (part-time) Student

RESEARCHERS AARNIO Janne M.Sc.(Tech.)

GEBUS Sébastien D.Sc. (Tech.)

ISOKANGAS Ari M.Sc. (Tech.)

LEIVISKÄ Tiina M.Sc. (Tech.)

MÄYRÄ Outi M.Sc. (Tech.)

NIVA Mikko M.Sc. (Tech.)

7ANNUAL REPORT 2007

NÄSI Jari D.Sc. (Geol.)

PAAVOLA Marko M.Sc. (Tech.)

PAJULAMPI Ulla M.Sc. (Tech.)

RAHKOLIN Vesa M.Sc. (Tech.)

RUUSKA Jari M.Sc. (Tech.)

RUUSUNEN Mika M.Sc. (Tech.)

SORSA Aki M.SC. (Tech.)

TOMPERI Jani M.Sc. (Tech.)

RESEARCH ASSISTANTS HAKA Jani Student

KEMPPAINEN Juha Student

LANGE Carl-Erik Student

PELTOKANGAS Riikka Student

SARASTO Ilari Student

TOLONEN Teppo Student

VAARA Juho Student

VÄHÄKANGAS Ville Student

ANNUAL REPORT 20078

2. EDUCATIONAL ACTIVITIES2.1 University CoursesIntroduction to Control EngineeringThe lectures were held over a period of five weeks, six hours per week in the autumn term. The course was for the students in the third year.

Lecturer: Professor Kauko Leiviskä

Contents:- goals of automation in industrial production- specifications and documentation of instrumentation- principles of measurements, analysers and sensors, application, installation and

purchase of different industrial instruments- introduction to characteristics, application and dimensioning of the final- control elements such as actuators, positioners, valves, dampers, pumps, and

motorsThere was no special textbook.

In laboratory exercises the principles of pressure, level and temperature measurements and controls were studied.

Process Control Engineering IThe lectures were held over a period of five weeks, six hours per week in the spring term. The participants were students in the third year. The exercises were four hours per week; two teachers were simultaneously present.


Contents:- basics of process models and dynamics- lumped parameter models- distributed parameter models- practical examples of different unit processes such as chemical reactors, distillation

columns and heat exchangers.There was no special textbook. Course home page: http://ntsat.oulu.fi/ps1/

In laboratory exercises modelling was studied with simulations.

Process Control Engineering IIThe lectures were held over a period of five weeks, six hours per week in the spring term. This course was for the students in the third year.


Contents:- statistical processing of measurement information- design of process experiments

�ANNUAL REPORT 2007

- regression analysis - test signals and dynamic modelling

There was no special textbook; some references were made to Diamond W.J., Practical Experiment Designs. Lifetime Learning Publications. Belmont, California, 1981. 348 p.

In laboratory exercises the experimental identification of a laboratory flow process was studied.

Process OptimisationThe course was held over a period of five weeks, ten hours per week in the autumn term. This course was for the students in the fourth year. MATLAB and interactive teaching methods were used. Students made a course portfolio; there was no exam.

Lecturers: Docent Leena Yliniemi and Senior Assistant Esko Juuso

Contents:- specification and formulation of optimisation problems of industrial processes and

plants- optimisation methods: unconstrained methods (univariate and multivariate func-

tions, first and second derivative methods, non-derivative methods, methods for sums of squares), penalty function methods, Lagrangian methods, constrained direct search, linear programming, and use of random numbers in optimisation

- non linear parameter estimation (fitting model functions to data)- use of MATLAB in optimisation and Matlab Optimization Toolbox

Course material:1. Edgar T F & Himmelblau D M (1988), Optimization of Chemical Processes. McGraw-

Hill 1988. ISBN 0-07-018991-9. 652 p.2. Home page: http://ntsat.oulu.fi/optimointi/.3. Jaako J (1997) Laskuharjoitusmoniste kurssiin 47434S Prosessien optimointi, Moniste

50, Prosessitekniikan osasto, Oulun yliopisto, Oulu 1997, 117 p., ISBN 951-42-4662-4. Internet Publication: http://ntsat.oulu.fi/optimointi/ps4_lhm.pdf(in Finnish).

4. Leiviskä K & Jaako J (1998) Kokeiluluentomoniste kurssiin 47434S Prosessien op-timointi. Prosessitekniikan osasto, Oulun yliopisto, Oulu. 91 p. Internet Publication: http://ntsat.oulu.fi/optimointi/ ps4_lm.pdf (in Finnish).

5. Ray W H & Szekely J (1973), Process Optimization. John Wiley & Sons, Inc., New York, 1973. 371 p.

6. Reklaitis G V, Ravindran A & Ragsdell K M (1983), Engineering Optimization - Methods and Applications. John Wiley & Sons 1983. ISBN 0-471-05579-4.

In the exercise work optimisation methods are applied to process problems.The course was held over a period of five weeks, ten hours per week in the autumn term. This course was for the students in the fourth year. MATLAB and interactive teaching methods were used. Students made a course portfolio; there was no exam.

ANNUAL REPORT 200710

Fuzzy-neuro Methods in Process AutomationThe lectures and computational exercises of this course were held over the period of five weeks, four hours of lectures and three hours of exercises per week and a seminar in the spring term. The participants were students in the fourth year.

Lecturer: Senior Assistant Esko Juuso

Exercises: Aki Sorsa

Contents:- principles of fuzzy set systems - fuzzy calculus- fuzzy reasoning - fuzzy control- adaptive fuzzy control - neural networks- fuzzy-neuro systems - genetic algorithms- linguistic equations - dynamic intelligent systems- intelligent fault diagnosis - cellular automation- data-based intelligent modelling - applications to process automation- software tools FuzzyCon and Matlab® (Fuzzy Logic Toolbox and Neural Network

Toolbox)Course material :1. Home page: http://ntsat.oulu.fi/Fuzzy_neuro/2. Babuska, R., Fuzzy Modelling for Control. Kluwer Academic Publishers, Boston,

1998.3. Brown, M. & Harris, C., Neurofuzzy Adaptive Modelling and Control. Prentice Hall,

New York, 1994.4. Driankov, D., Hellendoorn, H. & Reinfrank, M., An Introduction to Fuzzy Control.

Springer, Berlin, 1993.5. Verbruggen, H. B., H.-J. Zimmermann & R. Babuska, Fuzzy Algorithms for Control,

Kluwer Academic Publishers, Boston, 1999.6. Zimmermann, H.-J., Fuzzy Sets Theory and its Applications. Kluwer, Dordrecht,

1991.7. Kosko, B., Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to

Machine Intelligence. Prentice Hall, Englewood Clifffs, New Jersey, 1992.8. Davis, L. (ed.), Handbook of Genetic Algorithms. Van Nostrand Reinhold, NewYork,

1991.In the exercise work the principles of fuzzy set systems, fuzzy control, neural networks and genetic algorithms were studied in Matlab-Simulink environment.The lectures and computational exercises of this course were held over a period of five weeks, four hours of lectures and three hours of exercises per week and a seminar in the spring term. The participants were students in the fourth year.

11ANNUAL REPORT 2007

Modelling and Control of Biotechnical ProcessesLectures (20 h) and exercises (15 h) were held during one period in the spring term.


Exercises: Researcher Aki Sorsa

Contents: - bioreactors: reactor types, kinetics and transfer phenomena - on-line measurements and analysers - bio- and software sensors - reactor modelling- cell level models and control mechanisms- unstructured and structured models- bioprocess control- examples

There was no special textbook. Course home page: http://ntsat.oulu.fi

2.2 ERASMUS Exchange Student ProgrammeThe laboratory has co-operation contracts under the Erasmus exchange programme with the following universities: University of Loughborough and University of Cranfield from England, University of Leuven from Belgium and University of Calabria, University of Naples and University of Palermo from Italy and with IFMA (Institute Francais De Mècanique Avancèe) from France. The contracts include both teacher and student ex-changes. During the year 2007 two students from IFMA and one student from University of Loughborough have studied in our laboratory.


3. RESEARCH3.1 International Projects3.1.1 COST E36: Modelling and Simulation in the Pulp and Paper Industry (K. Leiviskä)The main objective of the action is to advance the development and application of simulation techniques in the pulp and paper manufacturing processes. This is to minimise environmental impact, and increase productivity and cost-competitiveness.The benefits will be the better understanding of the operation of the processes and their control. Thus solutions can make progress for currently pending problems in the paper industry: design of improved or new product properties, higher paper quality, optimised wet end chemistry, better runnability and low environmental impact.Operation occurs in three working groups: Modelling and simulation of the pulping and paper production processes; online use of simulation in the pulp and paper production processes; use of simulation software in the pulp and paper production processes. Ten European countries are involved and the length of the project is four years.

3.1.2 Nature-Inspired Smart Information Systems (NiSIS)(K. Leiviskä)NiSIS is a European Project under the Co-ordinated Action (CA) scheme with the fol-lowing overall mission aims:

- to co-ordinate multi-disciplinary studies and research endeavours into the devel-opment and utilisation of intelligent paradigms in advanced information systems design

- to extend investigations into emerging new areas inspired by nature, both at biological (i.e. micro) and behavioural (i.e. macro) levels for visionary concepts of information processing and architectures

NiSIS operates via three Focus Groups and several co-ordinated activities including Task Forces for new areas. The main event in 2007 was the 3rd Annual Symposium arranged in St. Julian’s, Malta, at the end of November.The Control Engineering Laboratory is one of the initiators of NiSIS.

3.1.3 Immune System Inspired Health Monitoring of Machinery using the Danger Theory(V. Vähäkangas, K. Leiviskä, J. Strackeljan, E. Juuso, S. Lahdelma)This is a NiSIS Task Force Project that used AbNET- algorithm for diagnosing machinery faults. The results were promising concerning the detection of roller bearing faults. Dam-aged rolling bearings were separated from the normal fault-free operation and other simulated fault classes. There are still problems and misclassifying with other fault classes


like unbalance, bent shaft and misalignment, because features of these faults are similar. The results were reported in the 3rd NiSIS Annual Symposium.

3.1.� European Sensor Network Architecture (ESNA)(M. Paavola, K. Leiviskä)ESNA-project aims to provide the necessary support for effective development of wireless sensor network applications: a standard architecture, technology and application-develop-ment guidelines, and proof-of-concept implementations.The Finnish National project is carried out with the consortium consisting of VTT and the Control Engineering Laboratory and two companies: VTI Technologies and Intar Oy. In the Control Engineering Laboratory, the main emphasis is on wireless automation so-lutions, their design and use. The research starts from the laboratory’s earlier know-how and experience on wireless automation and existing and new test environments. The new environment includes wireless transmitters and sensors which are implemented in the small scale steam boiler. It consists of the water storage tank, boiler, and pipe lines. In the steam boiler process, four measurements, three temperature measurements and one pressure measurement are monitored. The monitoring system has three transmitters and one gateway which uses OPC interface passing the measurement information to the LabVIEWTM development system. The national funding is from Tekes.

3.1.� Exchange Student ProjectsTuning of Linguistic Equations for Failure Mode Identification using genetic Algo-rithms (O. R. Yahyaoui, S. Gebus, E. Juuso, M. Ruusunen)Early fault mode identification presents a great deal of interest for defect prevention or for planning maintenance operations. In case of non-linear systems, the amount and accuracy of measured parameters can be an issue. Redundant variables can result in a reduced generalization and a subsequent loss of predictive ability of the model. In this project, a test rig equipped with multiple sensors was used to simulate different fault types. While fault identification is based on linguistic equations, this approach is enhanced by the use of genetic algorithms for selection of variables. This approach enabled proper identification of faults with a minimum amount of sensors.


3.2 Research Projects3.2.1 Implementing Intelligent Systems on Multiparameter Barkhausen Noise Measurements (INTELBARK) (A. Sorsa, K. Leiviskä)This three-year project is financed by the Finnish Academy and it is performed as a joint project with Tampere University of Technology and Oulu University. Institute of Materials Science at TUT is the project coordinator. In this research project, intelligent methods are implemented in multi-parameter Barkhausen Noise (BN) measurements in order to increase understanding about correlations between complex multi-parameter BN data, to simulate the phenomenon and to exploit the information in the industrial quality control measurements.

3.2.2 Towards Utilization of CO2 as a green and Versatile Commod-ity Chemical: Clean Synthesis of Methanol and Dimethyl Carbonate (CO2UTIL) (O. Mäyrä, K. Leiviskä)This four-year project is financed by the Finnish Academy and it is a co-operation project between the University of Oulu, the Department of Process and Environmental Engi-neering, the Åbo Akademi University, the Laboratory of Industrial Chemistry and the University of Bourgogne/ Centre National de la Recherche Scientific.This project aims at developing a sustainable production process for the synthesis of methanol and DMC using carbon dioxide as a raw material. The process will result in value enhancement of a secondary resource from anthropogenic source, while minimiz-ing environmental impacts. The new process will also result in waste minimization for the industry via utilizing waste CO2 and reducing the hazard of solvents and chemicals conventionally used, while developing new innovative and sustainable products that have high economic value. To facilitate this goal, the project intends to identify new, effective catalysts for methanol and DMC syntheses, and explore safe and environmentally sound reaction routes and energy-efficient processes.The Control Engineering Laboratory contributes to the dynamic simulation of the proc-ess chains starting from waste CO2 and ending up with different products. The work is based on the earlier experience on the reformer-reduction simulation case. The models will utilize the experimental findings of other groups. The Laboratory also contributes to control and process optimization issues.

1�ANNUAL REPORT 2007

3.2.3 Control Potential of Different Operating Methods in Small-scale Wood Pellet Combustion (COPECOM)(M. Ruusunen, K. Leiviskä)This project is a part of ERA-NET Bioenergy Consortium. It is a co-operation between two Finnish universities (Tampere University of Technology and University of Oulu), one Swedish university (University of Växsjö) and two companies (MBIO-Energiteknik Ab and HT Enerco Oy).The main objective of the project is to straighten out the possible benefits of a small-scale pellet burner based on gasification compared to a conventional small scale pellet burner. The comparison includes both theory and practice with the use of the state of the art feedback control. The possible benefits are concerned with the reliability, cost ef-fectiveness, burning efficiency and emissions. A minor objective is to find out in theory if the small-scale gasification can be utilized in combination with the main heating function for minor power production.The project includes combustion trials with two burners in two major market boilers from Sweden and Finland and in one laboratory boiler with optimum burning geometry and constant draft. Thus, the experiments will also include the interaction between the burner and the combustion chamber geometry. The processes will be modelled, in ad-dition to physical modelling, from trial run measurements. With the aid of these models, the state of the art control methods for the burners will be developed. The trials include runs with and without feedback control.The national funding is from Tekes.

3.2.� Hydrogen Production for Fuel Cells by Bioethanol Reforming (J.Aarnio, M. Ohenoja, K. Leiviskä)This project is done in co-operation with the Department of Process and Environmen-tal Engineering and the Department of Electrical and Information Engineering from the University of Oulu and the Laboratory of Industrial Chemistry from Åbo Akademi University The project is concerned with hydrogen production by reforming bioethanol in a catalytic membrane reactor. The produced hydrogen is purified and used in fuel cells. The study is concerned with all units in the production chain: reforming in low temperatures, its separation and purification and the fuel cell technology. The role of Control Engineering Laboratory is in the dynamic modelling of separate processes and the whole production chain. Tekes is financing the project.


3.2.� Control and Optimisation in Biological Water Treatment (BioConOpti)(U. Pajulampi, J. Rita, E. Juuso, K. Leiviskä)This is a co-operation project with Kuopio University finaced by Tekes Symbio-pro-gramme. Industrial partners represent the paper industry and bring additional financing to the project.Biological water treatment depends strongly on changes in inlet water quality. Changes in biological state effect on the purification result and subsequent process phases. The objective of the project is to develop a model based optimization and control concept for detecting process conditions and comparing control actions to improve process operation. On-line measurements and laboratory analysis are combined to build indirect measure-ments and intelligent dynamic models. Uncertainty handling is an essential part of the models. The concept is tested in connection to actual industrial purification processes.

3.2.6 TuotantoPro/Tuotanto2010: Operational Decision Making in the Process Industry (Multidisciplinary approach)(T. Ahola, O. Mäyrä, A. Sorsa, S. Gebus, K. Leiviskä)This is a large consortium project including VTT, four University partners and several companies. It started in 2005 with the name Tuotanto 2010 and continues now as Tuo-tantoPro. Financing comes from Tekes and the companies.The project aims to develop the overall model for the industrial data streams, and support the development of computer systems both in production and maintenance organizations. In the project, the Control Engineering Laboratory, University of Oulu, is responsible for Work Package 2: “Compress and Combine Data”. Other partners are research groups at the University of Jyväskylä, the Helsinki University of Technology and the Tampere University of Technology. The grouping techniques developed earlier in the Universities of Oulu and Jyväskylä developed further, and especially Oulu worked with a new method based on genetic algorithms and PCA. The applications and experiences concerning indirect measurements were collected in a report that is available in project documentation. Both Oulu’s and HUT’s groups have worked on process state recogni-tion. The Oulu group developed a technology for the bi-stable bioprocess co-operating also with Work Package 3 on the modelling side. Testing has utilized data from several example processes. Simulation data was available from the simple bioprocess for water purification, the laboratory-scale reforming-reduc-tion process and from a paper machine simulator. Testing also utilized real paper machine data from earlier projects collected for studies on web break detection.


3.2.7 Regengas - Hybrid Reforming Process for the Recycling of greenhouse gases and for Upgrading in the Reduction and Combustion processes ( O. Mäyrä, J. Ruuska, K. Leiviskä)The share of the worldwide emissions of CO2-gas from the energy production and metal manufacturing is estimated to be around 40-50 %. The solutions developed to decrease emissions in both industries have quite seldom been able to adapt outside the target processes. New kinds of arrangements for the recycling of the gas flows of the combus-tion- and reduction processes using reforming seem to make it possible to have partly closed gas circulation and therefore to reduce the amount of the greenhouse gases. The critical technological challenge in the circulation concept is to develop a hybrid process that connects the energy-saving reforming, which has flexible raw materials, and the gasification of biomass.The aim of the project is to develop the hybrid process that is presented above. The results are going to be verified by doing laboratory tests with the laboratory equipment, which will be constructed to be like the explained process. The target is to verify the results that were calculated/simulated in the earlier project, closed gas circulation’s reduction- and combustion processes and utilisation of CO2, (CO2H2), which was funded by TEKES.Partners are the University of Oulu/ Process Metallurgy, Mass and Heat Transfer Proc-ess and Control Engineering from University of Oulu and Heat Engineering from Åbo Akademi, National Technology Agency of Finland (TEKES), Outokumpu Technology Oy, EHOVOC Oy and Neste Oil Oyj.The project finished in 2007

3.2.8 MATTA- On-line Quality Control as a Tool for Quality Assurance and Production Management (J. Ruuska, K. Leiviskä)Surface inspection data contains numerical knowledge about type, location and seriousness of error. Customer requirement knowledge is included now in the codes that describe the end use classes. In each of these classes a certain error rate is accepted. This infor-mation needs to be formalized, so that it can be compared. The target is to develop a description method as universal as possible for combined surface inspection data, which could be used in the tools of planning, monitoring and reporting.Partners are the University of Oulu/Control Engineering Laboratory, Outokumpu Stain-less Oy and National Technology Agency of Finland (TEKES).The project finished in 2007


3.2.� Production of Demanding Steel Products by Advanced Ladle Metallurgy and Casting (VAATIVA)(J. Ruuska, K. Leiviskä)Production of demanding steel products by advanced ladle metallurgy and casting is a joint research project by Rautaruukki Oyj, Imatra Steel Oy Ab and Outokumpu Stainless Oy. The main goal of the project is to enable production of new and demanding steel products according to corporate product strategies by utilizing modern ladle metallurgy and casting technology. Improving cost efficiency, quality producing ability and reliability of deliveries have an essential role in the project to retain and improve the competitive-ness of the steel industry.Control Engineering’s research in this project is focused on the modelling of IF-steel’s vacuum treatment and control development for the vessel. Partners are the University of Oulu, Rautaruukki Oyj, Imatra Steel Oy Ab, Outokumpu Stainless Oy, Helsinki University of Technology and National Technology Agency of Finland (TEKES).The project finished in 2007

3.2.10 STOKERI- Advanced Control of Small-scale Stoker Fired Boilers 2(M. Ruusunen)Stoker burners are used for small-scale energy production, where a typical heat output varies between 10 – 2000 kW. Burners in this scale are mainly designed for the use of biomass as a fuel, for example wood chips, wood pellets and fuel peat. Combustion is often non-optimal due to the lack of proper monitoring and control methods, and because of strongly changing power requirements and fuel quality. This may results in decreased efficiency with high pollution levels.In this research, new monitoring and control alternatives are explored in order to de-velop a control framework for small-scale stoker fired boilers. The study is first focused on identification of important variables and characteristics of the combustion process. Attempts are then made to replace some expensive measurements utilising the soft sensor approach, followed by the development of an inferential control strategy. To cope with changing process conditions, synthesis of advanced adaptation mechanisms and conventional control methods are also studied. At every stage, combustion experiments are to be conducted with a commercial stoker fired boiler to test results in practice. Results of this project can be further utilised in the development of automated control systems for small-scale combustion units.The first stage of this project was financed by TEKES, Veljekset Ala-Talkkari Oy, Masa-Tuote Ky and ProDevice Oy. TEKES, Veljekset Ala-Talkkari Oy, LL-Automaatio Oy and Insinööritoimisto Jari Luoma Ky financed the second stage started on 1.11.2005. The research is realised in co-operation with VTT Prosessit, Jyväskylä. The project belongs to


the technology programme “Small-scale production and use of wood fuels 2002-2006”, organised by TEKES.The project finished in 2007.

3.3 Industrial Projects3.3.1 KemOpti - Optimisation and Automatic Tuning Methods for Kemira Dosage Tools(V. Rahkolin, M. Niva, J. Tomperi, I. Sarasto, T. Leiviskä, E. Juuso, K. Leiviskä)The aim of the project is to develop new features for generic dosage tools for water treatment chemicals. These tools consist of controllers, on-line soft sensors and an end user’s support system. Process phenomena, effects of the chemicals and data analysis are essential in this study. Multiobjective optimisation was used in the tuning of controllers for the chemical treatment. Controllers developed in process simulators were tested in water treatment applications in municipal water works and in pulp and paper mills. Results have been very good. Controllers work well and they can keep the quality of outgoing water in the set point value. Several measuring devices have been compared and tested in the laboratory and in a mill. The KemOpti-project is financed by Kemira Oyj and TEKES.

3.� Other Projects3.�.1 Intelligent Dynamic Simulation with Uncertainty (E. Juuso)Dynamic LE models are extended to fuzzy inputs. The arguments of the scaling functions are obtained by fuzzy arithmetic, and the scaling is done with a fuzzy extension of the classical interval analysis. Three applications have been studied:

- The simulator of a batch cooking process consists of interactive models for alkali, lignin and dissolved solids. The alkali concentration is decreasing during the cook-ing, and the change in absolute figure is decreasing with increasing H-factor and decreasing alkali level. As the differences in operating conditions affect the speed of change, the models were adapted with a speed factor that depends on the H-factor and alkali level. The simulator calculates every time to the end of the cooking sequence on the basis of the cooking liquor analyser and various process measurements by the automation system. The simulator is well suited for early forecasting of cooking result: residual alkali, lignin and dissolved solids.

- The simulator of fed-batch enzyme fermentation process consists of three interact-ing dynamic LE models. Each model has three versions, i.e. an own version for each phase of the fed-batch fermentation process. Steady state methods with dynamic structures were used in developing these linguistic equation models. With this simulator, it is possible to predict values of dissolved oxygen concentration, oxygen transfer rate and concentration of carbon dioxide in the exhaust gas through the


whole process, using only the values of the control variables as inputs. - In the model of a fluidised bed granulator used in production of pharmaceuti-

cals, the main input variables are the humidity difference between incoming and outgoing air, temperature difference between inflowing air and granule and the rate of inflowing air. The final output is the estimated granule size but the overall model contains also dynamic models for temperature and humidity. The simulator combines several models which are specific to the operating conditions.

Extension to fuzzy LE models provides useful information about uncertainties of the forecasted results. The complexity of the models is increased only slightly with the new system based on the extension principle and fuzzy interval analysis.

3.�.2 Intelligent Condition Monitoring(E. Juuso)Machine condition monitoring enables a reliable and economical way of action for main-tenance operations in modern industrial plants. Increasing the number of measurement points and more demanding problems requires automatic fault detection. Advanced signal processing methods exposes failures earlier and provides information on suitable operating conditions of machines. Intelligent methods have been used in model based fault diagnosis for combining several features. This approach has been used for develop-ing a cavitation indicator for a Kaplan water turbine and condition indices for supporting rolls of a lime kiln and very fast rotating bearings. The cavitation indicator provides good results throughout the power range. The indicator also provides warnings of possible risk on short periods of cavitation. All the supporting rolls are analysed with the same system. Surface damages are clearly detected and also an early indication of the friction increase is achieved. For fast rotating bearings the analysis was based on three frequency ranges. Normal conditions, unbalance and bearing faults, both inner and outer race, are detected by the condition index and the features. Short sample times and relatively low requirements for the frequency ranges make this approach feasible for on-line analysis and power control. Uncertainties can be taken into account by extending the feature calculations and classification rules to fuzzy set systems.This research was done in co-operation with the Mechatronics and Machine Diagnostics Laboratory of the University of Oulu and Otto-von-Guericke Universität Magdeburg, Institut für Mechanik.


3.� Doctoral Thesis Projects3.�.1 Process Analysis and Management of Wood Handling Plant(A.Isokangas)The thesis contains the results from wood handling plant; how to control the process to minimise the use of raw material still optimising the log cleanliness for next process stages. Data survey techniques have been emphasised in real process data modelling. Work also contains the results of interactions and correlations of variables of debarking. The effects of capacity and single log properties to chip quality are also presented. According to the research work, upper level control strategy has been proposed to compensate the raw material disturbances enabling properly debarked logs and excellent quality chips for next process stages.Time schedule 2008/2009.

3.�.2 Integration of Intelligent Systems in Development of Smart Adaptive Systems(E. Juuso)Both expertise and data can be integrated in the development of intelligent systems. A large number of feasible solutions can be developed for small, specialised systems, but developing truly adaptive, and still understandable, systems for highly complex systems require more compact approaches in the basic level. Linguistic equation (LE) approach originating from fuzzy logic is an efficient technique for these problems. Insight into the process operation is maintained since all the modules can be assessed by expert knowledge, and scaling functions, denoted as membership definitions and relative measurements to appropriate operating areas. The LE approach increases the performance by combining various specialised models in a case-based approach. The LE approach is successfully ex-tended to dynamic simulation, and used in intelligent controller design and fault diagnosis. The integration of intelligent systems is based on understanding the different tasks of smart adaptive systems: modelling, intelligent analysers, detection of operating conditions, control and intelligent actuators. The system integration leads to a hybrid system: fuzzy set systems move gradually to higher levels, neural networks and evolutionary computing are used for tuning, and the whole system reinforced with efficient statistical analysis, signal processing and mechanistic modelling and simulation. The thesis concentrates on the LE methodology as a building tool for smart adaptive applications. Several applications are discussed. The thesis is planned to be completed in autumn 2008.

3.�.3 Modelling for Management of LD-Kg-converter(J. Rruuska)Work done in two research projects, KONVERTO and KONTROL, is reported in this thesis research. In KONVERTO temperature and additional material models were de-


veloped in co-operation with Ruukki Production, Raahe. In KONTROL several measure-ments were tested in Ruukki Production, Raahe. Especially results from new splashing measurement are discussed. In addition to the research done during research projects a monitoring system for BOF (basic oxygen furnace) is proposed.The doctoral thesis should be finished by 2009.

3.�. � Measurement and Control Methods for Small-Scale Biomass Combustion(M. Ruusunen)The dissertation focuses on modelling and control of combustion based on process measurements. The main objective is to search and design reliable indicators for behav-iour and quality of the biomass combustion by analysing the information for example from temperature sensors. The enriched information is then utilised in development of model-based control strategy. The primary process variables to be monitored are derived from the measurement of single or multiple secondary variables. Information from these inferential measurements is fused using mathematical modelling, such as modified fuzzy principal component regression. As a result, the estimated value of a primary variable can be utilised further in monitoring and control. A novel control method for biomass combustion is developed and demonstrated in this dissertation project. The concept utilises data-based modelling approach for combustion state monitoring. The information is further integrated with the feedback control strategy, where knowledge of optimal operating conditions and instant heat output levels are used for stabilising the burning rate and excess air. This soft sensor approach was chosen to explore possibilities to replace more complex, slower or expensive measurements needed for proper boiler control automation at distributed energy production.The research stages are design of combustion experiments, process identification, model development and testing, integration of a final control strategy, control tests, analysis of results and final reporting. Data for analysis is collected from the biomass combustion experiment campaigns with several small-scale, grate fired units intended for heat pro-duction.Simulations and practical test result with a 300 kW commercial boiler indicate significantly higher total efficiency and somewhat lower emissions in different operating conditions, when comparing typical set point control methods to the developed model-based control strategy. The structure of the new control method has also portable properties, based on the data analysis of a smaller 30 kW boiler measurements. The results can further help to design cost-effective control systems that continuously monitor and optimise com-bustion conditions in small-scale grate fired boilers. This, in turn, makes the minimisation of the total energy usage and emissions possible at annual level. Expected dissertation date 05/2010.


4 THESISDegree for Diploma Engineer Isohanni Jukka Halkaisulinja 1:n ajo-ohjelman tietokoneavusteinen suunnittelu. Computer aided running order planning for the slitting line 1.

Kokkonen Matti Terässulattoprosessien saannot ruostumattoman teräksen valm-istuksessa.

Yields of the steel works processes in the making of stainless steel.

Koskinen Kari Kuitulinjan tunnuslukujen valvonta. The monitoring of the characteristics in a fiberline.

Laurila Jyrki IT-palveluiden jatkuvuuden hallinta terästeollisuuden tuotantoyk-sikössä

Continuity of information service in metal industry.

Lielahti Matti Päällystyskoneen radan hallinnan kehittäminen Development of web handling for the coating machine.

Liukkonen Mika Älykkäät menetelmät aaltojuotosprosessin mallinnuksessa Intelligent methods in the modelling of the wave soldering

process.

Luukka Tuomas Jatkuvavalukoneen kokillin pinnankorkeuden säädön analysointi ja virittäminen diagnostiikkajärjestelmällä.

The analysis and tuning of mould level control using diagnostic system.

Niva Mikko Monitavoiteoptimointi kemikaaliannostelussa Multiple criteria optimization in chemicals dosage.

Peltokangas Riikka Säätimien viritysmenetelmien vertailu teollisuusprosessien säädössä.

Comparison of tuning methods for industrial process control.

Pirnes Markku Kalenteroinnin profiloinnin hallinta. Calender profiling.

Pirttimaa Mika Juotepastanpainon painolaadun säätö ja tilastollinen prosessino-hjaus.

Solder paste printing statistical process control of the printing quality.

Pulkkinen Jenni Further testing of a new model to predict NO emission by CFD from marine diesel engines.

Salmela Aki Päällystetyn paperin tasalaatuisuuden parantaminen ja pintaviko-jen vähentäminen.

Quality development of coated paper.


Skön Jukka-Pekka Laskennallisten menetelmien soveltaminen QSAR-analyysissä, case: Yhdisteiden karsinogeenisuuden mallintaminen neu-roverkoilla

Using computational methods in QSAR analysis, case: modelling compound carsinogenicity using the neural networks.

Vähäkangas Ville Artical immune systems in fault diagnosis.

Degree for Doctor of TechnologyKeski-Säntti Jarmo Neural Networks in the Production Optimization of a Kraft

Pulp Bleach Plant.

AbstractBleaching is an essential process in chemical pulp production for better pulp brightness and longer life expectancy. However, it creates costs such as chemicals, energy, equipment, and loss of yield. Non-linear reactions and several process variables, with interactions, make large plants complicated to model and optimize. As an expensive process bleaching has been a natural target of optimization, but there is still the need to either improve these methods or consider the optimization problem from a new point of view. The aim of this thesis was to develop production optimization methods for pulp bleach-ing, so that they are practical, usable on-line, easy to tune, and transferable. According to our assumption, neural networks could provide a practical optimization method by combining analytical knowledge with real data. In this kind of problem, the load sharing concept, recognizing interactions in chemical usage and the serial multi-stage nature of the process can simplify the task. The related work in bleaching optimization was studied as well as multi-stage serial proc-ess solving in principle, related optimization methods and especially neural networks in optimization. The data was collected during normal mill operation and modelled using neural networks. Optimization was performed based on visualizing the neural network models.The results showed that backpropagation neural networks are capable of modelling parts of the bleach plant and also the entire bleaching operation to such an extent that they are useful in the optimization. The modelling and the tuning can be performed without a profound knowledge of the system, but the process is slower and less reliable. Moving a trained neural network to another mill is inadvisable. It is more reasonable just to transfer the knowledge of variables and network structure. The important factor in on-line produc-tion optimization is the stabilization of the disturbances and a well-controlled operation towards a more economical state. Generally, more than half of the total chemicals should be used in the first bleaching stage D0 and the remaining load should be divided so that the dosage at the D1 is about 30% higher than in the D2 stage.Key words: backpropagation, bleaching, fuzzy cognitive maps, kraft pulp, load sharing, modelling, neural networks, optimization


Näsi Jari Intensified Use of Process Measurements in Hydrometallurgical Zinc Production Processes.

AbstractThis thesis pursues to evidence that it is possible to get information on the behaviour of a complex chemical process by data-based analysis, even though the accurate reaction chemistry is not known.In the hydrometallurgical zinc production process, metallic zinc is produced by reducing it from aqueous solution. The essential part of the process is the purification of zinc sul-phate solution, where all elements nobler than zinc are removed by deposition from the solution. These elements lower the efficiency of the electric current drastically and cause zinc dissolution even in the smallest amounts. Process monitoring supplies a remarkable amount of on-line measurement data and analysis information. This makes it possible to use data-based methods for the evaluation of deposition reactions.The purpose of this thesis was not to specify reaction equations, but to evaluate which of the known reactions will occur in different process conditions. This was done by diagnosing the purification process of zinc sulphate solution and by combining measurement infor-mation with reaction models. An increased understanding of process stability also affects solution purification costs. The results gave new information about the purification process of zinc sulphate solution and its accelerating and decelerating components. The second target was to develop a modular, model-free method of signal validation and estimation, suitable for implementation in the control system in the form of a simple, configurable algorithm. Combining measurements confidence level-based information with fuzzy logic provides a compact system that is easily implemented in the process automation system. The algorithm developed was tested in a direct leaching process, where the combination of fast on-line sensors and accurate reference measurement was needed. Measurement data came from an operational zinc plant, so the amount of factory testing was strictly limited. Data evaluation was based on long-term variations in process conditions, possible disturbances and breakdowns of the measurement devices.


5. PARTICIPATIONSProfessor Kauko Leiviskä participated in

- COST ACTION E36: Modelling and Simulation in the Pulp and Paper Industry, Working Group Meeting, München, 6-8 May 2007

- ERA-NET Bioenergy Small-scale Combustion Workshop, Jyväskylä, 23 May 2007- COST E36: International Workshop on Towards Improved Productivity via Advanced

Modelling and Simulations, Manchester, UK, 8 November 2007- NISIS Grand Challenges & Impact Workshop, 6–7 September 2007, Hotel

Schweizerhof, Aachen-Lichtenbusch, Germany,- 3rd European Symposium on Nature-Inspired Smart Information Systems,

St. Julians, Malta.

Chief Engineer Leena Yliniemi participated in- Seminar of ENMR- European Network of Mining Regions, Girona, Spain, 22-23

January- Seminar of ENMR- European Network of Mining Regions, Kiruna, Sweden, 12-14

March- Automation 07 Seminar Days, Helsinki, 27-28 March- FinnMATERIA- Fair and Seminar giving the presentation “Oulu Mining Cluster-

Mining Education by Networking”, 7-9 May Jyväskylä- FEM - 6th Fennoscandian Exploration and Mining, Rovaniemi, 27-29 November- Seminar for Mine Geologists, Rovaniemi, 27 November, giving the presentation “

Professional Development Programme for Mining Professionals”

Researcher Ari Isokangas participated in- PaPSaT annual seminar. August 2007, Turku, giving a presentation “Image and Sound

Analysis Defining the State of the Debarking Drum”

Senior Assistant Esko Juuso participated in- Automation 07 Seminar Days, 27-28 March 2007, Helsinki, giving a presentation

“Intelligent Indicators in Integration of Condition Monitoring and Control”.- 2nd World Congress on Engineering Asset Management and 4th International

Conference on Condition Monitoring - WCEAM-CM 2007, 11-14 June 2007, Harrogate, UK, giving two presentations “Advanced Condition Monitoring for Lime Kilns” and “Feature Extraction for Vibration Analysis of Cavitation in Kaplan Water Turbines”, and a part of the keynote presentation “Advanced Signal Processing and Fault Diagnosis in Condition Monitoring”.

- EUROSIM 2007 – 6th EUROSIM Congress on Modelling and Simulation, Ljubljana, Slovenia, 9-14 September, giving two presentations “Forecasting Batch Cooking Results with Intelligent Dynamic Simulation” and “Intelligent Short Term Scheduling of a Production Cell with Parallel Facilities” and acting as chair of one session.

- SIMS 2007 – 48th Conference on Simulation and Modelling, Gothenburg (Särö)


30-31 October, 2007, giving a presentation “Intelligent Modelling of a Fluidised Bed Granulator used in Production of Pharmaceuticals” and acting as chair of one session.

Researcher Outi Mäyrä participated in- IFAC/IFORS/IMACS/IFIP 11th Symposium on Large Scale Complex Systems Theory

and Applications, Gdansk, Poland, 23-25 July.- Graduate School for Energy Science and Technology (EST) yearly seminar, Espoo,

Finland, 27-28 August

Researcher Jari Ruuska participated in- IFAC Symposium on Automation in Mining, Mineral and Metal Industry, Quebec,

Canada, 21-23 August

Researcher Mika Ruusunen participated in - BIOS BIOENERGIESYSTEME GmbH, Graz University of Technology, research visit,

16-20 January Graz, Austria- ERA-NET Bioenergy, Small-Scale Combustion - Workshop, 23-24 May, Jyväskylä,

Finland, giving a presentation “Control Potential of Different Operating Methods in Small-scale Wood Pellet Combustion (COPECOM)”

- Puun pienpoltto - vähäpäästöistä teknologiaa ja liiketoimintaa: päätösseminaari, 5-6 June, Jyväskylä, Finland, giving a presentation “Polton säädöllä parempaan palamisen hallintaan”

- Graduate School for Energy Science and Technology (EST) yearly seminar, 27-28 August, Espoo, Finland

Researcher Aki Sorsa participated in - 17th European Symposium on Computer Aided Process Engineering (ESCAPE

17), Bucharest, Romania, 27-30 May


6 PAPERS AND PUBLICATIONS Ahola T., Juuso E. & Leiviskä, K.: Variable Selection and Grouping in a Paper Machine Application, Int. J. of Computers, Communications & Control, Vol. II (2007), No. 2, pp. 111-120

Juuso E. K.:Forecasting batch cooking results with intelligent dynamic simulation. - Proceedings of the 6th EUROSIM Congress on Modelling and Simulation, 9-13 Sept. 2007, Ljubljana, Slovenia, CD-ROM (B. Zupancic; R. Karba & S. Blazic, Eds.) , Argesim, Austria, 2007, 8 pp. ISBN 978-3-901608-32-2

Juuso E. K.:Intelligent modelling of a fluidised bed granulator used in production of pharmaceuticals. - Conference Proceedings, The 48th Scandinavian Conference on Simulation and Model-ling, Göteborg (Särö) 30-31 October, 2007 (P. Bunus, D. Fritzson, C. Fuhrer, Eds.) Linköping Electronic Conference Proceedings nro 27. Linköping, Sweden. Linköping University Electronic Press 2007, pp. 101-108. http://www.ep.liu.se/epc/027/

Juuso E. & Ahola T.:Case-based reasoning with fuzzy logic and linguistic equations. - Workshop Proceeding of the seventh international conference on case-based reasoning ICCBR’07, Belfast, Northern Ireland, 13-16 August 2007 (D. Wilson & D. Khemani, Eds.), pp. 59-68.

Juuso E. K. & Jagdev H. S.: Intelligent short term scheduling of a production cell with parallel facilities. - Proceed-ings of the 6th EUROSIM Congress on Modelling and Simulation, 9-13 September 2007, Ljubljana, Slovenia, CD-ROM (B. Zupancic; R. Karba & S. Blazic, Eds.), Argesim, Austria, 2007, 9 pp. ISBN 978-3-901608-32-2

Juuso E. & Lahdelma S.:Älykkäät indikaattorit kunnonvalvonnan ja säädön integroinnissa. - Automaatio07 semi-naaripäivät 27. - 28.3.2007, Helsinki. Suomen Automaatioseura ry 2007. 6 s.

Juuso E. & Lahdelma S.:Advanced condition monitoring for lime kilns. - Proceedings of The Second World Con-gress on Engineering Asset Management and the Fourth International Conference on Condition Monitoring WCEAM-CM 2007, 11-14 June 2007, Harrogate, UK, CD-ROM, Coxmoor, 2007, pp. 931-942.

Juuso E., Lahdelma S. & Vähäoja P.:Feature extraction for vibration analysis of cavitation in Kaplan water turbines. - Proceed-ings of The Second World Congress on Engineering Asset Management and the Fourth International Conference on Condition Monitoring WCEAM-CM 2007, 11-14 June 2007, Harrogate, UK, CD-ROM, Coxmoor, 2007, pp. 943-952.


Lahdelma S. & Juuso E.:Advanced signal processing and fault diagnosis in condition monitoring. – Proceedings of The Second World Congress on Engineering Asset Management and the Fourth In-ternational Conference on Condition Monitoring WCEAM-CM 2007, 11-14 June 2007, Harrogate, UK, CD-ROM, Coxmoor 2007, pp. 1155-1168.

Lahdelma S. & Juuso E.:Advanced signal processing and fault diagnosis in condition monitoring. Insight - Non-Destructive Testing and Condition Monitoring, 2007, vol. 40, nro 12, pp. 719-725. http://www.atypon-link.com/BINT/loi/insi

Lahdelma S., Vähäoja P. & Juuso E.:Detection of cavitation in Kaplan water turbines. - 2007 Arctic Summer Conference on Dynamics, Vibrations amd Control, 6-10 August 2007, Ivalo. Final Programme and Book of Abstracts (E. Keskinen & T. Karvinen, Eds.), Tampere University of Technology 2007, 1 p.

Lahdelma S., Vähäoja P. & Juuso E.:Detection of cavitation in Kaplan water turbines. – Proceedings of 2007 Arctic Summer Conference on Dynamics, Vibrations amd Control, 6-10 August 2007, Ivalo, CD-ROM (E. Keskinen & T. Karvinen, Eds.), Tampere University of Technology 2007. 13 pp.

Leiviskä K.:From measurements to control. POHTO Course “Measurements and Control in Metal-lurgical Processes, April 20, 2007 (In Finnish).

Leiviskä K.:Data-based modelling in web break sensitivity indicator. In: COST E36: International Workshop on Towards Improved Productivity via Advanced Modelling and Simulations, Manchester, UK, November 8, 2007, pp. 30-34. ISBN 13-978-0-9556152-1-4. University of Manchester.

Leiviskä K., Strackeljan J. & Vähäkangas,V.:Immune System Inspired Health Monitoring of Machinery. 3rd European Symposium on nature-inspired Smart Information Systems, St. Julians, Malta. (available at http://www.nisis.risk-technologies.com/events/symp2007/papers/BE11_13925_p_Leiviska_Strackeljan.pdf

Mäyrä O., Ahola T. & Leiviskä K.: Time delay estimation in large databases. 11th Symposium on Large Scale Complex Systems Theory and Applications, Gdansk, Poland, 23-25 July 2007, CD-ROM, IFAC 2007, 6p.

Paavola M.: Wireless Technologies in Process Automation – A Review and an Application Example. University of Oulu, Control Engineering Laboratory, Report A No 33, December 2007. 38 p. ISBN 978-951-42-8705-3.


Ruuska J., Ollila, S. & Leiviskä, K.:Model-based monitoring of basic oxygen furnace, IFAC Symposium on Automation in Min-ing, Mineral and Metal Industry, Quebec, Canada, August 21-23, IFAC 2007, p. 47-51.

Ruusunen M.:Effect Of Automatic Control Technologies on Emission Reduction in Small-scale Combus-tion, In: (Eds. Hytönen Kati & Jokiniemi Jorma) Reduction of fine particle emissions from residential wood combustion - final report, Workshop in Kuopio on 22-23 May 2006. University of Kuopio, Report Series 3/2007. p. 18-22. ISSN 0786-4728.

Sorsa A. & Leiviskä K.: State Detection of a Wastewater Treatment Plant. In: Plesu V. and Agachi P.S. (Eds.): 17th European Symposium on Computer Aided Process Engineering, Bucharest, Romania, 27-30 May 2007, 1337-1342.

7. VISITSLeena Yliniemi has visited

- AGH University of Science and Technology, Krakow Poland, 10-13 October

Esko Juuso has visited- School of Mechanical, Aerospace and Civil Engineering, The University of

Manchester, 15 June 2007.- International Institute of Acoustics and Vibration, Cranfield University, School of

Engineering, Department of Process and Systems Engineering, 18-19 June 2007.- Faculty of Electrical Engineering, University of Ljubljana, Slovenia, 9-13 September

2007.- Department of Analytical and Applied Chemistry and Department of Biotechnol-

ogy of Arkhangelsk State Technical University, Arkhangelsk, Russia, 12-13 November 2007.


8. OTHERS

Professor Kauko Leiviskä has been- Dean of Technical Faculty in the University of Oulu - Member of Board, University of Oulu- Head of Control Engineering Laboratory- Member of Integrating Board, NiSIS CA-network- Chairman of Campus Futurus Steering Group, University of Oulu- Chair of Co-ordinating group for Neighbourhood Cooperation - Member of Board, Biocenter Oulu- Member of Board and Vice-Chair, Infotech Oulu - Member of Board and Vice-Chair, Thule Institute- Member and Vice-Chair of Library Board, University of Oulu- Member of Board, Chydenius-Institute- Member of Executive Board, Center for Advanced Steels Research, University of

Oulu- Member in the Programme Board of Management, International Ph.D. Programme

in Pulp and Paper Science and Technology- Member of Steering Group for ESR-projects in Technology, University of Kuopio

Vice-Member of Board, Learning and Research Services, University of Oulu- IFAC contact person of Finnish NMO - Member of IPC, International Conference on Informatics in Control, Automation

and Robotics (ICINCO 2007), Angiers, France, 9-12 May 2007- Member of IPC, IASTED International Conference on Intelligent Systems and

Control (ISC 2007), Cambridge, Massachusetts, USA, 19–21 November 2007 - Member of IPC, International Conference on Artificial Neural Networks, (ICANN

07), Porto, Portugal, 9-13 September 2007- Member of IPC, ICINCO 2007 - 4th International Conference on Informatics in

Control, Automation and Robotics. Angers, France, 9-12 May, 2007.- Member of IPC, PULPAPER 2007, Helsinki, 5-7 June 2007- Member of IPC, IASTED International Conference on Computational Intelligence,

CI 2007, Banff, Canada, July 2-4 2007- Member of IPC, 11th IFAC/IFORS/IMACS/IFIP Symposium on Large Scale Systems:

Theory and Applications, Gdansk, Poland, 23-25 July 2007- Member of IPC, 4th International Federation of Automatic Control Conference

on Management and Control of Production and Logistics, Sibiu, Romania, 27-30 September 2007

- Member of IPC, Control Systems ’08 – Vancouver, British Columbia, Canada, 16-18 June 2008

- Member of IPC. 2007 American Control Conference – ACC 07 – 11-13 July 2007 New York, USA


Chief Engineer Leena Yliniemi has been- Member of the Automation Foundation of the Finnish Society of Automation- Vice Member of Board in the University of Oulu- Vice Member of the Council of the Department of Process and Environmental

Engineering- Vice member of Campus Futurus Steering Group in the University of Oulu- Member of IFAC Control Education Committee- Member of IFAC Networking Systems- Vice Member of the Council in the City of Oulu- Member of the Energy Board in the City of Oulu- Member of the Technical Board in the City of Oulu

Senior Assistant Esko Juuso has been - Chair of Scandinavian Simulation Society (SIMS)- Secretary of Board (EUROSIM)- Chair of Finnish Simulation Forum (FinSim)- Chair of Test Processes and Analysis Workgroup for the Northern Center for

Electronics Manufacturing NTC. - Member of IPC 6th EUROSIM Congress on Modelling and Simulation (EUROSIM

2007), Ljubljana, Slovenia- Member of IPC 48th Conference on Simulation and Modelling (SIMS 2007),

Gothenburg, Sweden- Member of IPC European Simulation and Modelling Conference (ESM 2007),

St. Julian’s, Malta- Member of IPC EUROSIM / UKSim 2008 Conference, Cambridge, UK- Member of International Scientific Advisory Committee CM-MFPT 2008,

Edinburgh, UK

Control Engineering Laboratory - University of Oulu methods and applications and COST E36 action on...

Documents

Transcript of Control Engineering Laboratory - University of Oulu methods and applications and COST E36 action on...