Control Engineering
Research group information
Unit and faculty
Contact information
Research group leader
- Professor
Research group description
Control Engineering research group focuses on the modeling and process control, sensor fusion, advanced data analysis and optimization. Emerging research themes are related to continuous model and soft sensor adaptation applications, model reliability assessment in model-based control systems, and predictive (simulation aided) optimization with uncertainties.
Methods to allow easy and automatic implementation and re-calibration of measurements into real environments are of interest, while research on robust and adaptive soft sensors utilizing data fusion continues.
In the context of AI methods, future development focuses on the enabling of more facile utilization of AI methods, especially the implementation and maintenance issues in dynamic processes, incorporation of expert knowledge; and the fusion of AI tools and process optimization methods.
Agriculture
Organic fertilizer recycling at farmscale (MAA-BIO I&II)
Target: Identification and control design for a high-rate bioreactor processing organic side streams and producing biogas.
Actions and results: Research included design of experiments, analysis of results, mass and energy balance calculations together with planning of control strategy and instrumentation for optimization of a bioprocess.
Project duration: 2017
Contact person: Professor Mika Ruusunen
Prediction of plant disease outbreak by advanced data analysis (MaDaKas)
Target: The accurate prediction system to help farmers to optimize the chemical spraying in crop farming.
Actions and results: The existing information about weather observations and the occurrence of the selected plant diseases, are utilized to develop a new prediction method for appearance of diseases. Without extra measurement, the existing information is upgraded by advanced data analysis.
Project duration: 01.03.2018 -31.03.2020
Contact person: Outi Ruusunen
Energy production and consumption
Bio-CCU - Creating sustainable value of the bio-based CO2
Target: The Bio-CCU project develops solutions for capturing biogenic CO2, green hydrogen production, sustainable CO2 utilization, and identifies the best business models for the value chains.
Actions and results: Control Engineering is focusing on process modeling and simulation of the process chains. Special attention is given to the CO2 separation from low-grade biogas, distributed production of H2, and chemical conversion of CO2. More info
Project duration: 01.08.2022 - 31.07.2024
Contact person: Dr. Markku Ohenoja
Digitalisaation työkalupakista eväät vähähiiliseen teollisuuteen (Majakka)
Target: Utilization of digitalisation in order to reduce carbon footprint of industrial processes.
Actions and results: Digitalization methods for better energy and raw material efficiency and extended life span of processing equipment. For example, the point cloud of mini pilot plant allows taking measures of current process equipment and designing new ones without visiting site. The point cloud has been utilized also in drones as navigation map. More info (in Finnish)
Project duration: 01.11.2019 - 31.12.2022
Contact person: Ari Isokangas
Highly Optimized Energy Systems (HOPE)
Target: To develop solutions to increase energy efficiency in energy networks and to promote co-operation within energy sector.
Actions and results: Joint project with several partners will develop tools and solutions for the multi‐objective optimization of energy systems by considering the operating conditions and uncertainty. This enables optimization to be adapted to the prevailing conditions, including use of advanced weather forecasts.
Project duration: 2020-2023
Contact person: Dr. Jari Ruuska
Biorefineries, pulp & paper
Utilization of sidestreams in biocircular economy - demonstration of continuous supercritical carbon dioxide extraction (BIOSFE)
Target: The project aims to demonstrate a novel continuous supercritical carbon dioxide extraction process for valorization of bio-based sidestreams at modern biorefineries.
Action and results: In this project, a process equipment is designed and manufactured to enable continuous operation. The workpackages include control and measurement design for the process in order to optimize its material and energy efficiencies. As a results, technical demonstrations are realized to show the effectiveness of the process development and control strategies. See video.
Project duration: 2020-2021
Contact person: Postdoctoral researcher Petri Österberg
Improve biorefinery operations through process intensification and new end products (BioSPRINT)
Target: Improve the efficiency of the purification and conversion of sugars from the hemicelluloses fraction of lignocellulosic biomass and to enable their transformation into new bio-based resins for substituting fossil based polymers in a range of applications.
Actions and results: Application of machine learning tools for heterogeneous catalyst synthesis, development of process simulation tools for the intensified biorefinery processes including upstream purification, catalytic conversion, downstream purification and polymerization.
Project duration: 2020-2024
Contact person: Dr. Markku Ohenoja
Operational eXcellence by Integrating Learned information into AcTionable Expertise (OXILATE)
Target: Enhancing intelligent services on complex systems, integrated in the customer’s operating context, reacting to the emerging customer needs for operationalized expertise in an agile manner.
Actions and results: Our research activities in this project aim to find flexible data pre-processing, process identification and modeling methods enabling efficient use of both the operational data and outputs from the digital twins. The developed models act as digital assistants e.g. for the process operators and supervisors in applications such as real-time process performance monitoring and prediction.
Project duration: 2020-2023
Contact person: Dr. Markku Ohenoja
Autonomous Processes Facilitated by Artificial Sensing Intelligence (APASSI)
Target: Development of measurement infrastructure and related services making autonomous large-scale industrial process possible.
Actions and results: Our research activities in this joint action were focused on adaptive modeling, advanced data analytics and intelligent measurements with case studies in papermaking and in mineral processing.
Project duration: 2019-2021
Contact person: Dr. Markku Ohenoja
Mining, mineral processing and metallurgy
EXCEED - Cost-effective, sustainable and responsible extraction routes for recovering distinct critical metals and industrial minerals as by-products from key European hard-rock lithium projects
Target: EXCEED develops, upscales & demonstrates cost-effective, sustainable and responsible extraction routes for recovering the CRMs and industrial minerals.
Actions and results: Our research is related to the development of a simulation model for the value chain from mine to refined CRMs, followed by an uncertainty assessment of the digital twin in model-based decision making. More info.
Project duration: 01.01.2023 - 31.12.2026
Contact person: Dr. Jari Ruuska
AI based plant optimization (AI_Opti)
Target: To screen and test the possible computational methods and the data sources to apply AI into mine to mill optimization. Aim is to develop a generalized framework.
Actions and results: In project with mining technology partner, a case study with chosen mine is studied and certain methodologies are tested in simulated environment. Tested data-based procedure using real data is reported in chosen form.
Project duration: 2021-2022
Contact person: Dr. Jari Ruuska
Autonomous Processes Facilitated by Artificial Sensing Intelligence (APASSI)
Target: Development of measurement infrastructure and related services making autonomous large-scale industrial process possible.
Actions and results: Our research activities in this joint action were focused on adaptive modeling, advanced data analytics and intelligent measurements with case studies in papermaking and in mineral processing.
Project duration: 2019-2021
Contact person: Dr. Markku Ohenoja
Intensified-by-Design (IbD®)
Target: Bridging the technological and knowledge gaps in the area of Process Intensification in processes involving solids.
Actions and results: We provided the control analysis toolbox for the holistic platform facilitating process intensification design and optimization. We also contributed to mineral processing case study with advanced process control and real-time model adaptation with evolutionary optimization.
Project duration: 2015-2018
Contact person: Dr. Markku Ohenoja
Water treatment
Circular economy of water in industrial processes (CEIWA)
The management of complex circular industrial water systems is a challenge that requires new tools to perform efficiently. CEIWA project develops solutions for digitalization, technology development, management of different pollutants, and legislative aspects. More info
Project duration: 01.04.2021 - 31.03.2023
Contact person: Jani Tomperi
Digitization of Water Utilities – Waste water networks data management and innovative applications (WWData)
The aim of WWData project is to help wastewater network management by developing new tools and methods for handling data in a safe way in e.g. cloud services. In the project, the most critical parameters are identified, the frequency of the measurements is evaluated against the needs for measurements in the networks, and it is investigated, what are the parameters outside of the networks that could be utilized in the management process. Also, a virtual sensor to estimate the wastewater flowrate at a gravitational sewer is developed utilizing the measurement data of a level sensor installed in the sewer. More information https://www.wwdata.fi
Project duration: 1.2.2020 - 31.5.2022
Contact person: Jani Tomperi
Measurement and automation
Operational eXcellence by Integrating Learned information into AcTionable Expertise (OXILATE)
Target: Enhancing intelligent services on complex systems, integrated in the customer’s operating context, reacting to the emerging customer needs for operationalized expertise in an agile manner.
Actions and results: Our research activities in this project aim to find flexible data pre-processing, process identification and modeling methods enabling efficient use of both the operational data and outputs from the digital twins. The developed models act as digital assistants e.g. for the process operators and supervisors in applications such as real-time process performance monitoring and prediction.
Project duration: 2020-2023
Contact person: Dr. Markku Ohenoja
Intensified-by-Design (IbD®)
Target: Bridging the technological and knowledge gaps in the area of Process Intensification in processes involving solids.
Actions and results: We provided the control analysis toolbox for the holistic platform facilitating process intensification design and optimization. We also contributed to mineral processing case study with advanced process control and real-time model adaptation with evolutionary optimization.
Project duration: 2015-2018
Contact person: Dr. Markku Ohenoja
Organic fertilizer recycling at farmscale (MAA-BIO I&II)
Target: Identification and control design for a high-rate bioreactor processing organic side streams and producing biogas.
Actions and results: Research included design of experiments, analysis of results, mass and energy balance calculations together with planning of control strategy and instrumentation for optimization of a bioprocess.
Project duration: 2017
Contact person: Professor Mika Ruusunen
Journal articles
[x] before a publication denotes ‘Julkaisufoorumi’-rating in publication year (https://www.tsv.fi/julkaisufoorumi/haku.php?lang=en).
2023
[1] Pätsi, T., Ohenoja, M., Kukkasniemi, H., Vuolio, T., Österber, P., Merikoski, S., Joutsijoki, H. & Ruusunen, M. (2023) Comparison of Single Control Loop Performance Monitoring Methods, Applied Sciences, Vol. 13(12), 6945, https://doi.org/10.3390/app13126945
[3] Ohenoja, M., Koistinen, A., Hultgren, M., Remes, A., Kortelainen, J., Kaartinen, J., Peltoniemi, M. & Ruusunen, M. (2023) Continuous adaptation of a digital twin model for a pilot flotation plant, Minerals Engineering, Vol. 198, 108081, https://doi.org/10.1016/j.mineng.2023.108081
[3] Ghorbani, Y., Zhang, S., Nwiala, G., Bourdeau, J., Safari, M., Hoseinie, S., Nwaila, P. & Ruuska, J. (2023) Dry laboratories – Mapping the required instrumentation and infrastructure for online monitoring, analysis, and characterization in the mineral industry. Minerals Engineering, 191, 107971. https://doi.org/10.1016/j.mineng.2022.107971
[1] Tomperi, J., Rossi, P. & Ruusunen, M. (2023) Estimation of wastewater flowrate in a gravitational sewer line based on a low-cost distance sensor. Water Practice & Technology. https://doi.org/10.2166/wpt.2022.171
[1] Sorsa, A., Ruusunen, M., Santa-aho, S. & Vippola, M. (2023) Sub-surface analysis of grinding burns with Barkhausen noise measurements. Materials, 16(1), 159. https://doi.org/10.3390/ma16010159
2022
[1] Rathnayake, B., Valkama, H., Ohenoja, M., Haverinen, J. & Keiski, R. (2022) Evaluation of nanofiltration membranes for the purification of monosaccharides: Influence of pH, temperature, and sulfates on the solute retention and fouling. Membranes, 12(12), 1210. https://doi.org/10.3390/membranes12121210
[1] Ruusunen, O., Jalli, M., Jauhiainen, L., Ruusunen, M. & Leiviskä, K. (2022) Identification of Optimal Starting Time Instance to Forecast Net Blotch Density in Spring Barley with Meteorological Data in Finland. Agriculture, 12(11), 1939. https://doi.org/10.3390/agriculture12111939
[1] Miettinen, J., Nikula, R., Keski-Rahkonen, J., Fagerholm, F., Tiainen, T., Sierla, S. & Viitala, R. (2022) Whitening CNN-Based Rotor System Fault Diagnosis Model Features. Applied Sciences, 12(9), 4411. https://doi.org/10.3390/app12094411
[1] Nikula, R., Ruusunen, M. & Böhme, S. (2022) On Training Data Selection in Condition Monitoring Applications—Case Azimuth Thrusters. Applied Sciences, Vol.12(8), 4024 https://doi.org/10.3390/app12084024
[3] Hämäläinen, H. & Ruusunen, M. (2022) Identification of a supercritical fluid extraction process for modelling the energy consumption. Energy, Vol.252(1), 124033. https://doi.org/10.1016/j.energy.2022.124033
[1] Uusitalo, P., Sorsa, A., Russo Abegão, F., Ohenoja, M. & Ruusunen, M. (2022) Systematic Data-Driven Modeling of Bimetallic Catalyst Performance for the Hydrogenation of 5-Ethoxymethylfurfural with Variable Selection and Regularization. Industrial & Engineering Chemistry Research, Vol. 61(14), 4752-4762. https://doi.org/10.1515/npprj-2021-0046
[1] Tomperi, J., Ohenoja, M., Ritala, R., Mäntylä, M., Graedde, M., Viitamäki, M., Juntunen, T. & Ruusunen, M. (2022) Mass-balance based soft sensor for monitoring ash content at two-ply paperboard manufacturing. Nordic Pulp & Paper Research Journal, Vol. 37(1). doi: 10.1515/npprj-2021-0046. https://doi.org/10.1021/acs.iecr.1c03995
2021
[0] Bertacchi, S., Ruusunen, M., Sorsa, A., Sirviö, A. & Branduardi, P. (2021) Mathematical Analysis and Update of ADM1 Model for Biomethane Production by Anaerobic Digestion. Fermentation, Vol.7(4), 237. doi: 10.3390/fermentation7040237.
[1] Juuso, E. (2021) Intelligent temporal analysis of coronavirus statistical data. Open Engineering, Vol. 11(1). doi: 10.1515/eng-2021-0118.
[3] Hietaharju, P., Pulkkinen, J., Ruusunen, M. & Louis, J. (2021) A stochastic dynamic building stock model for determining long-term district heating demand under future climate change. Applied Energy, Vol. 295. doi: 10.1016/j.apenergy.2021.116962.
[1] Karioja, K., Juuso, E. & Nissilä, J. (2021) Some further studies about generalised spectral norms. Insight - Non-Destructive Testing and Condition Monitoring, Vol. 53(6), pp. 362-369. doi: 10.1784/insi.2021.63.6.362.
[1] Nikula, R., Ruusunen, M., Keski-Rahkonen, J., Saarinen, L. & Fagerholm, F. (2021) Probabilistic Condition Monitoring of Azimuth Thrusters Based on Acceleration Measurements. Machines, Vol. 9(2):39. doi: 10.3390/machines9020039.
[1] Airaksinen, S., Tuovinen, T., Vuolio, T., Laukka, A., Heikkinen E., Riekki, E. & Fabritius, T. (2021) Oxide scale formation of EN 1.4622 and EN 1.4828 stainless steels during annealing and descaling behavior in neutral electrolytic pickling. Steel Research International, Vol. (). doi: 10.1002/srin.202100366.
2020
[-] Ruusunen, O., Jalli, M., Jauhiainen, L., Ruusunen, M. & Leiviskä, K. (2020) Data Analysis in Moving Windows for Optimizing Barley Net Blotch Prediction. Journal of Advanced Agricultural Technologies, Vol. 7(2), pp. 38-42. doi: 10.18178/joaat.7.2.38-42.
[1] Ohenoja, M. & Leiviskä, K. (2020) Observations on the Parameter Estimation Problem of Polymer Electrolyte Membrane Fuel Cell Polarization Curves. Fuel Cells, Vol. 20(5), pp. 516-526. doi: 10.1002/fuce.201900155.
[1] Juuso, E. (2020) Expertise and Uncertainty Processing with Nonlinear Scaling and Fuzzy Systems for Automation. Open Engineering, Vol. 10(1). doi: 10.1515/eng-2020-0080
[1] Tomperi, J., Isokangas, A., Tuuttila, T. & Paavola, M. (2020) Functionality of turbidity measurement under changing water quality and environmental conditions. Environmental Technology (United Kingdom), Vol. ##(##), pp. ###-###. doi: 10.1080/09593330.2020.1815860.
[1] Nikula, R., Paavola, M., Ruusunen, M. & Keski-Rahkonen, J. (2020) Towards online adaptation of digital twins. Open Engineering, Vol. 10(1). doi: 10.1515/eng-2020-0088.
[1] Nikula, R. & Leiviskä, K. (2020) Roller Leveler Monitoring Using Acceleration Measurements and Models for Steel Strip Properties. Machines, Vol. 8(3). doi: 10.3390/machines8030043.
[1] Ruusunen, O., Jalli, M., Jauhiainen, L., Ruusunen, M. & Leiviskä, K. (2020) Advanced data analysis as a tool for net blotch density estimation in spring barley. Agriculture, Vol. 10(5). doi: 10.3390/agriculture10050179.
[1] Valta, A., Ruusunen, M. & Leiviskä, K. (2020) On-line moisture content estimation of saw dust via machine vision. Open Engineering, Vol. 10(1). doi: 10.1515/eng-2020-0035.
[1] Ruuska, J., Nikula, R., Ruhanen, E., Kauppi, J., Kauvosaari, S. & Kosonen, M. (2020) Data analysis of a paste thickener. Open Engineering, Vol. 10(1). doi: 10.1515/eng-2020-0038.
[1] Vuolio, T., Visuri, V., Sorsa, A., Ollila, S. & Fabritius, T. (2020) Application of a genetic algorithm based model selection algorithm for identification of carbide-based hot metal desulfurization. Applied Soft Computing, Vol. 92, 106330. doi: 10.1016/j.asoc.2020.106330
[3] Nikula, R., Karioja, K., Pylvänäinen, M. & Leiviskä, K. (2020) Automation of low-speed bearing fault diagnosis based on autocorrelation of time domain features. Mechanical Systems and Signal Processing, Vol. 138, 106572. doi: 10.1016/j.ymssp.2019.106572
2019
[1] Tomkowski, R., Sorsa, A., Santa-Aho, S., Lundin, P. & Vippola, M. (2019) Statistical Evaluation of Barkhausen Noise Testing (BNT) for Ground Samples. Sensors, Vol. 19(21), 4716. doi: 10.3390/s19214716
[1] Santa-Aho, S., Laitinen, A., Sorsa, A. & Vippola, M. (2019) Barkhausen Noise Probes and Modelling: A Review. Journal of Nondestructive Evaluation, Vol. 38(4), 11 p. doi: 10.1007/s10921-019-0636-z
[1] Tomperi, J. & Leiviskä, K. (2019) Utilizing variable selection methods in modelling potable water quality. Water Science and Technology: Water Supply, 19(4), p. 1187-1194. doi: 10.2166/ws.2018.173
[1] Vuolio, T., Visuri, V.V., Sorsa, A., Paananen, T. & Fabritius, T. (2019) Genetic algorithm‐based variable selection in prediction of hot metal desulfurization kinetics. Steel Research International, 90(8). doi: 10.1002/srin.201900090
[1] Hietaharju, P., Ruusunen, M., Leiviskä, K. & Paavola, M. (2019) Predictive optimization of the heat demand in buildings at the city level. Applied Sciences, 9(10), 1994. doi: 10.3390/app9101994
[1] Sorsa, A., Santa-Aho, S., Aylott, C., Shaw, B.A., Vippola, M. & Leiviskä, K. (2019) Case depth prediction of nitrided samples with Barkhausen noise measurement. Metals, 9(3), 325. doi: 10.3390/met9030325
[1] Hietaharju, P., Ruusunen, M. & Leiviskä, K. (2019) Enabling demand side management: heat demand forecasting at city level. Materials, 12(2), 202. doi: 10.3390/ma12020202
[1] Ohenoja, M., Ruusunen, M. & Leiviskä, K. (2019) Hierarchical control of an integrated fuel processing and fuel cell system. Materials, 12(1), 21. doi: 10.3390/ma12010021
[1] Nikula, R., Karioja, K., Leiviskä, K. & Juuso, E. (2019) Prediction of mechanical stress in roller leveler based on vibration measurements and steel strip properties. Journal of Intelligent Manufacturing, 30(4), p. 1563-1579. doi: 10.1007/s10845-017-1341-3
2018
[0] Ohenoja, M., Sorsa, A. & Leiviskä, K. (2018) Model structure identification for fuel cell polarization curves. Computers, 7(4), 60. doi: 10.3390/computers7040060
[1] Mäyrä, O., Ruusunen, M., Jalli, M., Jauhiainen, L., & Leiviskä, K. (2018) Plant disease outbreak ‒ prediction by advanced data analysis. SNE – Simulation Notes Europe, 28(3), p. 113-115. doi: 10.11128/sne.28.sn.10431
[1] Tomperi, J. (2018) Utilizing optical monitoring to predict the effluent quality in the activated sludge processes. SNE – Simulation Notes Europe, 28(3), p. 89-92. doi: 10.11128/sne.28.sn.10423
[1] Koistinen, A. (2018) Monitoring and control in mining. SNE – Simulation Notes Europe, 28(3), p. 81-84. doi: 10.11128/sne.28.sn.10421
[1] Ohenoja, M., Boodhoo, K., Reay, D., Paavola, M. & Leiviskä K. (2018) Process control in intensified continuous solids handling. Chemical Engineering & Processing: Process Intensification, 131, 59-69. doi: 10.1016/j.cep.2018.07.008
[1] Hietaharju, P., Ruusunen, M. & Leiviskä K. (2018) A dynamic model for indoor temperature prediction in buildings. Energies, 11(6), 1477. doi: 10.3390/en11061477
[1] Santa-aho, S., Sorsa, A., Wartiainen, J., Lundin, P., Suominen, L., Jokiaho, T., Honkanen, M., Leiviskä, K., & Vippola, M. (2018) Surface layer characterization of shot peened gear specimens. Materials Performance and Characterization, Vol. 7(4). doi: 10.1520/MPC20170169
[1] Lindblad, J., Routa, J., Ruotsalainen, J., Kolströn, M., Isokangas, A. & Sikanen, L. (2018) Weather based moisture content modelling of harvesting residues in the stand. Silva Fennica, Vol. 52(2), 16 p. doi: 10.14214/sf.7830
[1] Juuso, E. (2018) An advanced teaching scheme for integrating problem-based learning in control education. Open Engineering, 8(1), pp. 41-49. doi:10.1515/eng-2018-0006
[1] Sorsa, A., Santa-aho, S., Wartiainen, J., Suominen, L., Vippola, M. & Leiviskä, K. (2018) Effect of shot peening parameters to residual stress profiles and Barkhausen noise. Journal of Nondestructive Evaluation, Vol. 37(10), 11 p. doi: 10.1007/s10921-018-0463-7
[1] Tomperi, J. & Leiviskä, K. (2018) Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality. Environmental Technology (United Kingdom), Vol.39(11), pp. 1442-1449. doi: 10.1080/09593330.2017.1331267
[1] Tomperi, J., Juuso, E., Kuokkanen, A. & Leiviskä, K. (2018) Monitoring a municipal wastewater treatment process using a trend analysis. Environmental Technology (United Kingdom), Vol. 39(24), 3193-3202. doi: 10.1080/09593330.2017.1375026
2017
[1] Tomperi, J., Koivuranta, E., Kuokkanen, A. & Leiviskä, K. (2017) Modelling effluent quality based on a real-time optical monitoring of the wastewater treatment process. Environmental Technology (United Kingdom), 38(1), p. 1-13. doi: 10.1080/09593330.2016.1181674
[1] Tomperi, J., Koivuranta, E. & Leiviskä, K. (2017) Predicting the effluent quality of an industrial wastewater treatment plant by way of optical monitoring. Journal of Water Process Engineering, 16, p. 283-289. doi: 10.1016/j.jwpe.2017.02.004
[0] Juuso, E. (2017) Intelligent performance analysis with a natural language interface. Management Systems in Production Engineering, 25(3), p. 168-175. doi: 10.1515/mspe-2017-0025.
[1] Tomperi, J., Piippo, S., Aikio, O., Luoma, T., Leiviskä, K. & Pongrácz, E. (2017) Sustainable waste management in Northern rural areas: Local utilisation of bio-wastes. International Journal of Energy and Environment (IJEE), 8(5), p. 365-374.
[0] Juuso, E. (2017) Intelligent control of a solar thermal power plant: adaption in varying conditions. Journal of Automation and Control Engineering, 5(1), p. 26-30. doi: 10.18178/joace.5.1.26-30.
2016
[2] Kulju, T, Paavola, M., Spittka H., Keiski R.L., Juuso E., Leiviskä, K., & Muurinen, E. (2016) Modeling continuous high-shear wet granulation with DEM-PB. Chemical Engineering Science, 142, p. 190-200. doi: 10.1016/j.ces.2015.11.032
[1] Tomperi, J., Koivuranta, E., Kuokkanen, A., Juuso, E. & Leiviskä, K. (2016) Real-time optical monitoring of the wastewater treatment process. Environmental Technology (United Kingdom), 37(3), p. 344-351. doi: 10.1080/09593330.2015.1069898
[2] Raatikainen, M., Skön, JP, Leiviskä, K. & Kolehmainen, M. (2016) Intelligent analysis of energy consumption in school buildings. Applied Energy, 165, p. 416-429. doi: 10.1016/j.apenergy.2015.12.072
[1] Laukka, A., Saari, J., Ruuska, J., Juuso, E. & Lahdelma, S. (2016) Condition-based monitoring for underground mobile machines. International Journal of Industrial and Systems Engineering, 23(1), p. 74-89. doi: 10.1504/IJISE.2016.075808
[2] Louis, J., Calo, A., Leiviskä, K., Pongrácz, E. (2016) Modelling home electricity management for sustainability: The impact of response levels, technological deployment & occupancy. Energy and Buildings, 119, p. 218-232. doi: 10.1016/j.enbuild.2016.03.012
[2] Ollakka, H., Ruuska, J. & Taskila, S. (2016) The application of principal component analysis for bioheapleaching process - Case study: Talvivaara mine. Minerals Engineering, 95, p. 48-58. doi: 10.1016/j.mineng.2016.06.009
[1] Tomperi, J., Juuso, E. & Leiviskä, K. (2016) Early warning of changing drinking water quality by trend analysis. Journal of Water and Health, 14(3), p. 433-442. doi: 10.2166/wh.2016.330
[2] Seppälä, P., Sorsa, A., Paavola, M., Ruuska J., Remes A., Kumar H., Lamberg P., & Leiviskä K. (2016) Development and calibration of a dynamic flotation circuit model. Minerals Engineering, 96–97, p. 168-176. doi: 10.1016/j.mineng.2016.07.004.
[1] Ohenoja M. & Leiviskä K. (2016) Performance evaluation of CD and MD control strategies utilizing image-based measurements. Nordic Pulp and Paper Research Journal, 31(3), p. 479-490. doi: 10.3183/NPPRJ-2016-31-03-p479-490
[2] Nikula, R., Ruusunen, M. & Leiviskä K. (2016) Data-driven framework for boiler performance monitoring. Applied Energy, 183, p. 1374-1388. doi: 10.1016/j.apenergy.2016.09.072
[1] Juuso, E. K. (2016) Modelling and Simulation in Adaptive Intelligent Control. SNE – Simulation Notes Europe, 26(2), p. 109-116. doi: 10.11128/sne.26.on.10338
[1] Karioja, K. & Juuso, E. K. (2016) Generalised spectral norms – a new method for condition monitoring. International Journal of Condition Monitoring, 6(1), p. 13-16. doi: 10.1784/204764216819257150
2015
[1] Järvinen, M.A., Paavola, M., Poutiainen, S., Itkonen, P., Pasanen, V., Uljas, K., Leiviskä, K., Juuti, M., Ketolainen, J. & Järvinen, K. (2015) Comparison of a continuous ring layer wet granulation process with batch high shear and fluidized bed granulation processes. Powder Technology, 275, p. 113-120.
[1] Isokangas, A., Ala-Kaila, K., Sorsa, A., Ohenoja, M. & Leiviskä, K. (2014) Characterisation of log loading process. Nordic Pulp & Paper Research Journal, 29(2), p. 195-200.
[1] Isokangas, A., Ala-Kaila, K., Ohenoja, M., Sorsa, A. & Leiviskä, K. (2014). Effect of log loading on the performance of wood room. Nordic Pulp & Paper Research Journal, 29(2), p. 201-210.
[1] Koivuranta, E., Keskitalo, J., Stoor, T., Hattuniemi, J., Sarén, M. & Niinimäki, J. (2014) A comparison between floc morphology and the effluent clarity at a full-scale activated sludge plant using optical monitoring. Environmental Technology (United Kingdom), 35(13), p. 1605-1610.
DOI: 10.1080/09593330.2013.875065
[1] Sorsa, A., Isokangas, A., Santa-aho S., Vippola, M., Lepistö, T. & Leiviskä, K. (2014) Prediction of residual stresses using partial least squares regression on Barkhausen noise signals. Journal of Nondestructive Evaluation 33: 43–50.
[1] Sorsa, A., Ruusunen, M., Leiviskä, K., Santa-aho, S., Vippola, M. & Lepistö, T. (2014) An attempt to find an empirical model between Barkhausen noise and stress. Materials Science Forum, Vol. 768-769, p. 209-216.
[-] Tomperi, J., Luoma, T., Pongrácz, E., Leiviskä, K. (2014) Energy potential of biodegradable wastes in Kolari. Pollack Periodica, 9(SUPPL. 1), p. 5-15.
[1] Tomperi, J., Juuso, E., Eteläniemi, M., Leiviskä, K. (2014) Drinking water quality monitoring using trend analysis. Journal of Water and Health, 12(2), p. 230-241.
[2] Santa-aho, S., Sorsa, A., Hakanen, M., Leiviskä, K., Vippola, M., Lepistö, T. (2014) Barkhausen noise-magnetizing voltage sweep measurement in evaluation of residual stress in hardened components. Measurement Science and Technology, 25(8).
[1] Rantamäki J., Isokangas A., Ala-Kaila K., Honkanen T. (2014). Estimation methods of log loading performance in industrial debarking for the kraft pulping process. Nordic Pulp & Paper Research Journal, 29(4), p. 592-598.
[1] Santa-aho, S., Sorsa, A., Nurmikolu, A., Vippola, M. Review of railway track applications of Barkhausen noise and other magnetic testing methods. Insight - Non-Destructive Testing and Condition Monitoring, 56(12), p. 657–663.
[1] Louis, J., Calo, A., Leiviskä, K., Pongrácz, E. (2014) A Methodology for Accounting the CO2 Emissions of Electricity Generation in Finland - The contribution of home automation to decarbonisation in the residential sector. International Journal on Advances in Intelligent Systems, 8(3&4), p. 560-571.
[-] Juuso, E. K. (2014) Intelligent Methods in Modelling and Simulation of Complex Systems. SNE – Simulation Notes Europe, 24(1), p. 1-10.
[1] Jaako, J. (2013) Controlling the didactic relation: a case in process engineering education. European Journal of Engineering Education. Published online: 13 Dec 2013. http://dx.doi.org/10.1080/03043797.2013.867315
[1] Juuso, E.K. & Lahdelma, S. (2013) Intelligent performance measures for condition-based maintenance. Journal of Quality in Maintenance Engineering, 19(3), p. 278-294.
[1] Järvinen, M.A., Paaso, J., Paavola, M., Leiviskä, K., Juuti, M., Muzzio, F. & Järvinen, K. (2013) Continuous direct tablet compression: Effects of impeller rotation rate, total feed rate and drug content on the tablet properties and drug release. Drug Development and Industrial Pharmacy 39 (11), p. 1802-1808.
[1] Koivuranta, E., Keskitalo, J., Haapala, A., Stoor, T., Sarén, M. & Niinimäki, J. (2013) Optical monitoring of activated sludge flocs in bulking and non-bulking conditions. Environmental Technology (United Kingdom), 34(5), p. 679-686. DOI:10.1080/09593330.2012.710410
[1] Ohenoja, M. & Leiviskä, K. (2013) Simulation study on usability of web imaging in a paper machine on-line estimation. Nordic Pulp and Paper Research Journal, 28(3), p. 407-414.
[0] Paavola, M., El Hagrasy A., Litster, J. & Leiviskä, K. (2013) 3D Population Balance Model for Continuous Twin Screw Granulator. Chemical Engineering Transactions 32, p. 2077-2082.
[1] Ruuska, J., Ollila S. & Leiviskä, K. (2013) The Possibility to Use Optical Emission Spectrometry for Identifying the Amount of Inclusions in Steels. Materials Science Forum, 762, p. 649-655.
[1] Sorsa, A., Leiviskä, K., Santa-aho S., Vippola M. & Lepistö T. (2013) An efficient procedure for identifying the prediction model between residual stress and Barkhausen noise. Journal of Nondestructive Evaluation, Vol. 32(4), p. 341-349.
[-] Tomperi, J., Pelo, M. & Leiviskä, K. (2013) Predicting the residual aluminum level in water treatment process. Drinking Water Engineering and Science, 6, p. 36-46, doi:10.5194/dwes-6-39-2013.
[2] Keskitalo, J. & Leiviskä, K. (2012) Application of evolutionary optimisers in data-based calibration of Activated Sludge Models. Expert Systems with Applications, 39(7), p. 6609-6617.
[1] Santa-aho, S., Vippola, M., Saarinen, T., Isakov, M., Sorsa, A., Lindgren, M., Leiviskä, K. & Lepistö, T. (2012) Barkhausen Noise characterization during elastic bending and tensile-compression loading of case-hardened and tempered samples. Journal of Materials Science, Vol. 47, p. 6520-6428.
[1] Santa-aho, S., Vippola, M., Sorsa, A., Latokartano, J., Lindgren, M., Leiviskä, K. & Lepistö, T. (2012) Development of Barkhausen noise calibration blocks for reliable grinding burn detection. Journal of Materials Processing Technology, Vol. 212(2), p. 408-416.
[1] Santa-aho, S., Vippola, M., Sorsa, A., Leiviskä, K., Lindgren, M. & Lepistö, T. (2012) Utilization of Barkhausen noise magnetizing sweeps for case-depth detection from hardened steel. NDT & E International, Vol. 52, p. 95-102.
[1] Santa-aho, S., Vippola, M., Sorsa, A., Lindgren, M., Latokartano, J., Leiviskä, K. & Lepistö, T. (2012) Optimized laser processing of calibration blocks for grinding burn detection with Barkhausen noise. Journal of Materials Processing Technology, Vol. 212(11), p. 2282-2293.
[1] Sorsa, A., Leiviskä, K., Santa-aho, S. & Lepistö, T. (2012) A data-based modelling scheme for estimating residual stress from Barkhausen noise measurements. Insight - Non-Destructive Testing and Condition Monitoring, Vol. 54(5), p. 278-283.
[1] Sorsa, A., Leiviskä, K., Santa-aho, S. & Lepistö, T. (2012) Quantitative prediction of residual stress and hardness in case-hardened steel based on the Barkhausen noise measurement. NDT& E International, Vol. 46, p. 100-106.
[0] Tomperi, J., Honkanen, M., Kallio, P., Leiviskä, K., Saarenrinne P., Joensuu I. & Piironen M. (2012) Digital Imaging and Piezo-dispenser Actuator in Automatic Flocculation Control. Sensors & Transducers Journal, Vol. 136, (1), p. 83-95.
[-] Skön J.-P., Johansson M., Kauhanen, O., Raatikainen, M., Leiviskä, K. & Kolehmainen, M. (2012) Wireless Building Monitoring and Control System. In: - (ed.) , -. World Academy of Science, Engineering and Technology 65. p. 706-711.
[-] Skön, J.-P., Johansson, M., Raatikainen, M., Haverinen-Shaughnessy, U., Pasanen, P., Leiviskä, K. & Kolehmainen, M. (2012) Analysing Events and Anomalies in Indoor Air Quality Using Self-Organizing Maps. International Journal of Artificial Intelligence 9: A12.
2011
Hiltunen, J., Heikkinen, E.-P., Jaako, J. & Ahola, J. (2011) Pedagogical basis of DAS formalism in engineering education. European Journal of Engineering Education, 36(1), p. 75-85. DOI:10.1080/03043797.2010.539677
Koskela, P., Paavola, M., Karjanlahti, J. & Leiviskä, K. (2011) Condition Monitoring of a Process Filter Applying Wireless Vibration Analysis. Sensors & Transducers. Vol. 128, no. 5.
Lahdelma, S. & Juuso, E. (2011) Signal processing and feature extraction by using real order derivatives and generalised norms. Part 1: Methodology. The International Journal of Condition Monitoring, Vol. 1(2), p. 46-53.
Lahdelma, S. & Juuso, E. (2011) Signal processing and feature extraction by using real order derivatives and generalised norms. Part 2: Applications. The International Journal of Condition Monitoring, Vol. 1(2), p. 54-66.
Ohenoja M. & Leiviskä, K. (2011) Multiple property cross direction control of paper machines. Modeling, Identification and Control, 32(3), p. 103-112.
Sorsa A. & Leiviskä, K. (2011) Simultaneous prediction of residual stress and hardness from Barkhausen noise signal. NDT World Review, Vol. 4, p. 78-83. (In Russian)
Keskitalo J., La Cour Jansen J. & Leiviskä, K. (2010) Calibration and validation of a modified ASM1 using long-term simulation of a full-scale pulp mill wastewater treatment plant. Environmental Technology (United Kingdom), 31(5), p. 555-566.
Ohenoja M. & Leiviskä, K. (2010) Validation of genetic algorithm results in a fuel cell model. International Journal of Hydrogen Energy, Vol. 35 (22), p. 12618-12625.
Rantonen, M., Frantti, T. & Leiviskä, K. (2010) Fuzzy Expert System for Load Balancing in Symmetric Multiprocessor Systems. Expert Systems with Applications 37(2010), 8711-8720.
Sorsa A., Leiviskä, K., Santa-aho S., Vippola M. & Lepistö T. (2010) A study on laser-processed grinding burn simulation and analysis on Barkhausen noise measurement. Insight - Non-Destructive Testing and Condition Monitoring, Vol. 52(6), p. 293-297.
Taskila S., Tuomola M., Kronlöf J., Ruuska J. & Neubauer P. (2010) Note-Preliminary applications of response surface modeling to the evaluation of optimal growth conditions for beer-spoiling Pediococcus damnosus. Journal of the Institute of Brewing, 116(3):211-214.
Gebus, S., Juuso, E. & Leiviskä, K. (2009) Knowledge-based linguistic equations for defect detection through functional testing of printed circuit boards. Expert Systems with Applications, 36 (1), p. 292-302.
Gebus, S., Leiviskä, K. (2009) Knowledge acquisition for decision support systems on an electronic assembly line. Expert Systems with Applications, 36 (1), p. 93-101.
Holck, P., Sorsa, A. & Leiviskä, K. (2009) Parameter identification in the activated sludge process. Chemical Engineering Transactions, Vol. 17, 1293-1298.
Liimatainen, H., Haapala, A., Tomperi, J. & Niinimäki J. (2009). Fibre floc morphology and dewaterability of a pulp suspension: role of flocculation kinetics and characteristics of flocculation agents. Bioresources 4 (2), p. 640-658.
Ahola, T., Juuso, E. & Leiviskä, K. (2007) Variable selection and grouping in paper machine application. International Journal of Computers, Communications and Control II (2007)2, 111-120.
Lahdelma, S. & Juuso, E. (2007) Advanced signal processing and fault diagnosis in condition monitoring. Insight: Non-Destructive Testing and Condition Monitoring, 49(12), p. 719-725.
Sorsa, A. & Leiviskä, K. (2007) State detection of a wastewater treatment plant. Computer Aided Chemical Engineering, Vol. 24, 1337-1342.
Ahola, T. & Leiviskä, K. (2005) Case-Based Reasoning in Web Break Sensitivity Evaluation in Paper Machine. Journal of Advanced Computational Intelligence and Intelligent Informatics 9(2005)5, 556-561.
Isokangas, A. & Leiviskä, K. (2005) Optimisation of wood losses in log debarking drum. Paperi ja Puu 87(5), p. 324–328.
Joensuu, I., Piironen, M. & Juuso, E. (2005) Dynamic simulator for dosing of water treatment chemicals. Computer Aided Chemical Engineering, 20 (C), p. 301-306.
Näsi, J. & Leiviskä, K. (2005) Solution filtration in cobalt removal process; detection of varying process conditions. Minerals Engineering 18(13-14). p. 1253-1258.
Juuso, E. K. (2004) Integration of intelligent systems in development of smart adaptive systems. International Journal of Approximate Reasoning 35:307–337. doi: 10.1016/j.ijar.2003.08.008.
Näsi, J. (2004) Statistical analysis of cobalt removal from zinc electrolyte using the arsenic activated process. Journal of Hydrometallurgy, 73. p. 123-132.
Ruuska J., Ollila S. & Leiviskä, K. (2004) Temperature and Additional Material Models for LD-KG converter. Materia 2/2004, 38-42.
Ruusunen M. & Leiviskä, K. (2004) Fuzzy modelling of carbon dioxide in a burning process. Control Engineering Practice, Vol. 12(5), p. 607-614.
Yliniemi, L., Koskinen, J. & Leiviskä, K. (2003) Data-driven fuzzy modelling of a rotary dryer. International Journal of Systems Science 34 (14-15) , p. 819-836.
Järvensivu, M., Juuso, E. & Ahava, O. (2001) Intelligent control of a rotary kiln fired with producer gas generated from biomass. Engineering Applications of Artificial Intelligence, 14 (5), p. 629-653.
Jarvensivu, M., Juuso, E. & Ahava, O. (200) Intelligent supervisory-level control of industrial processes. Paperi ja Puu/Paper and Timber, 82 (6), p. 386-391.
Book chapters
[x] before a publication denotes ‘Julkaisufoorumi’-rating in publication year (https://www.tsv.fi/julkaisufoorumi/haku.php?lang=en).
2021
[2] Vuolio, T., Pesonen, O., Sorsa, A. & Santa-aho, S. (2022) Neural Network Model Identification Studies to Predict Residual Stress of a Steel Plate Based on a Non-destructive Barkhausen Noise Measurement. In: Datta S., Davim J.P. (eds) Machine Learning in Industry. Management and Industrial Engineering. Springer, Cham. doi:10.1007/978-3-030-75847-9_2
2018
[3] Ohenoja, M., Paavola, & Leiviskä, K. (2018) Control design tools for intensified solids handling process concepts. In: Advances in Systematic Creativity: Creating and Managing Innovations, eds. Chechurin, L., & Collan, M. Palgrave Macmillan, p. 167-180. doi: 10.1007/978-3-319-78075-7_11
2017
[2] Mäyrä, O. & Leiviskä, K. Modelling in methanol synthesis. In: Methanol: Science and Engineering, eds. Basile, Angelo; Dalena, Francesco, Elsevier, p. 475-492. doi: 10.1016/B978-0-444-63903-5.00017-0.
[1] Jantunen, E., Karaila, M., Hästbacka, D., Koistinen, A., Barna, L., Juuso, E., Punal Pereira, P., Besseau, S. & Hoepffner, J. Application system design - Maintenance. In: IoT Automation: Arrowhead Framework, ed. Delsing, Jerker, CRC press, p. 247-280.
2016
[1] Juuso, E. & Galar D. Intelligent real-time risk analysis for machines and process devices. In: Current Trends in Reliability, Availability, Maintainability and Safety: An Industrial Perspective, eds. Kumar, Uday; Ahmadi, Alireza; Verma, Ajit Kumar; Varde, Prabhakar, Lecture notes in mechanical engineering, Springer publishing company, p. 229-240. doi: 10.1007/978-3-319-23597-4_17.
2015
[1] Paavola, M. & Seppälä, P. Wireless networks in underground mines. In: Industrial wireless sensor networks : Monitoring, Control and Automation, eds. Budampati, Ramakrishna; Kolavennu, Soumitri, Woodhead Publishing Series in Electronics and Optical Materials, p. 107-123.
Paavola, M., Ruusunen, M., Sorsa, A. & Leiviskä, K. (2012) Information theoretic approach to improve performance of networked control systems. In: Advances in Intelligent Data Analysis XI, eds. Holmen J., Klawonn F., & Tucker A., Springer: Berlin Heidelberg, Lecture Notes in Computer Science, Vol. 7619, p. 253-263.
Keiski, R.L., Ojala, S., Huuhtanen, M., Kolli, T. & Leiviskä, K. (2011) Partial oxidation (POx) processes and technology for clean fuel and chemical production. In: Advances in clean hydrocarbon fuel processing: Science and technology, ed. Khan MR., Woodhead Publishing Ltd., 262-286.
Paavola, M. & Leiviskä, K. (2010) Wireless Sensor Networks in Industrial Automation. In: Factory Automation, ed.: Javier Silvestre-Blanes, INTECH, March 2010. ISBN: 978-953-307-024-7. ISBN 978-953-307-024-7.
Ruusunen, M. (2010) Advanced combustion power stabilization method for a grate-fired biomass boiler. In: Szentannai P. (Ed.), Power Plant Applications of Advanced Control Techniques. ProcessEng Engineering GmbH, Wien. p. 113-134.
Sorsa, A., Peltokangas, R. & Leiviskä, K. (2010) Case studies for genetic algorithms in system identification tasks. In: Kacprzyk J, Hadjiski M and Sgurev V (eds.) Intelligent Systems: From Theory to Practice. Studies in Computational Intelligence, Vol. 299, p. 243-260.
Filip, F.-G. & Leiviskä, K. (2009) Large-Scale Complex Systems. Springer Handbook of Automation, Nof, S. (editor). Springer Verlag, 2009, Berlin, Heidelberg. ISBN 978-3-540-78830-0. 619-635.
Juuso, E. K. (2009) Tuning of large-scale linguistic equation (LE) models with genetic algorithms. In: Kolehmainen, M. (ed.), Revised selected papers of the International Conference on Adaptive and Natural Computing Algorithms - ICANNGA 2009, Kuopio, Finland, Lecture Notes in Computer Science, Springer-Verlag, Heidelberg, vol. LNCS 5495, pp. 161–170. doi: 10.1007/978-3-642-04921-7_17.
Sorsa A. & Leiviskä, K. (2009) Feature selection from Barkhausen noise data using genetic algorithms with cross-validation. In: Kolehmainen M, Toivanen P and Beliczynski B (eds.) ICANNGA 2009, Lecture Notes in Computer Science, Vol. 5495, p. 213-222.
Leiviskä, K., Jämsä-Jounela, S.L., Olli, J. & Äyrämö S. (2008) Computational methods and techniques. In: Operational decision making in the process Industry: Multidisciplinary approach (ed. Teemu Mätäsaho). VTT Research Notes 2442. Espoo 2008, 42-75.
2005
Leiviskä, K. (2005) Problem Definition – From Applications to Methods. In “Do Smart Adaptive Systems Exist?” by Gabrys, B., Leiviskä, K., Strackeljan, J., (Eds.). Springer-Verlag Berlin Heidelberg 2005, 19-26.
Leiviskä, K. & Yliniemi, L. (2005) Design of Adaptive Fuzzy Controllers. In: “Do Smart Adaptive Systems Exist?” by Gabrys, B., Leiviskä, K., Strackeljan, J., (Eds.). Springer-Verlag Berlin Heidelberg 2005, 251-266.
2004
Leiviska, K. (2004) Adaptation in intelligent systems: Case studies in process industries. In: Machine Intelligence - Quo Vadis. Eds. P. Sincák; J. Vascák & K. Hirota. Advances in Fuzzy Systems - Applications and Theory vol. 21. World Scientific 2004, 259-273.
2001
Leiviskä, K. (2001) Basics of Soft Computing Methods. In: Leiviskä, K., (editor): Industrial Applications of Soft Computing. Paper, Mineral and Metal Processing Industries. Physica-Verlag, Heidelberg, New York, 2001, 3-22.
Leiviskä, K. (2001) Soft Computing Applications in Mineral and Metal Industries. In: Leiviskä, K., (editor): Industrial Applications of Soft Computing. Paper, Mineral and Metal Processing Industries. Physica-Verlag, Heidelberg, New York, 2001, 23-34.
Leiviskä, K. (2001) Soft Computing Applications in Pulp and Paper Industries. In: Leiviskä, K., (editor): Industrial Applications of Soft Computing. Paper, Mineral and Metal Processing Industries. Physica-Verlag, Heidelberg, New York, 2001, 35-46.
Leiviskä, K., Juuso, E. & Isokangas, A. (2001) Intelligent Modelling of Continuous Pulp Cooking. In: Leiviskä, K., (editor): Industrial Applications of Soft Computing. Paper, Mineral and Metal Processing Industries. Physica-Verlag, Heidelberg, New York, 2001, 147-158.
Doctoral dissertations
[32] Nikula, Riku-Pekka (2022) Automated methods for vibration-based condition monitoring of rotating machines
[31] Hietaharju, Petri (2021) Predictive optimization of heat demand utilizing heat storage capacity of buildings
[30] Tomperi, Jani (2018) Predicting the treated wastewater quality utilizing optical monitoring of the activated sludge process
[29] Koskela, Pekka (2018) Energy-efficient solutions for wireless sensor networks
[28] Raatikainen, Mika (2016) Intelligent knowledge discovery on building energy and indoor climate data.
[27] Ohenoja, Markku (2016) Computational methods for exploiting image-based data in paper web profile control.
[26] Skön, Jukka-Pekka (2015) Intelligent information processing in building monitoring systems and applications.
[25] Juuso, Esko (2013) Integration of intelligent systems in development of smart adaptive systems : linguistic equation approach.
[24] Ruusunen, Mika (2013) Signal correlations in biomass combustion – an information theoretic analysis.
[23] Sorsa, Aki (2013) Prediction of material properties based on non-destructive Barkhausen noise measurement.
[22] Ruuska, Jari (2012) Special measurements and control models for a basic oxygen furnace (BOF).
[21] Räsänen, Teemu (2011) Intelligent information services in environmental applications.
[20] Paavola, Marko (2011) An efficient entropy estimation approach.
[19] Isokangas, Ari (2010) Analysis and management of wood room.
[18] Keski-Säntti, Jarmo (2007) Neural networks in the production optimization of a kraft pulp bleach plant.
[17] Näsi, Jari (2007) Intensified use of process measurements in hydrometallurgical zinc production processes.
[16] Ahola, Timo (2006) Intelligent Estimation of Web Break Sensitivity in Paper Machines.
[15] Gebus, Sébastien (2006) Knowledge-Based Decision Support Systems for Production Optimization and Quality Improvement in the Electronics Industry.
[14] Lindfors, Juha (2002) A Modern Learning Environment for Control Engineering.
[13] Frantti, Tapio (2001) Timing of Fuzzy Membership Functions from Data.
[12] Pesonen, Lasse T. T. (2001) Implementation of Design to Profit in a Complex and Dynamic Business Context.
[11] Karppanen, Erkki (2000) Advanced Control of an Industrial Circulating Fluidized Bed Boiler Using Fuzzy Logic.
[10] Yliniemi, Leena (1999) Advanced Control of a Rotary Dryer.
[09] Huusko, Antti (1997) Milled Peat Production Optimisation, a Study of the Development of the Planning system.
[08] Jaako, Juha (1996) The Extension of Multilevel Flow Modelling.
[07] Kaarela, Kari (1996) Enhancing Communication of Plant Design Knowledge.
[06] Sopenlehto-Pelkonen, Taina (1996), Customer Focused Process Applications and Utilization Studies of Special Instruments in Pulp and Paper Industry.
[05] Kess, Pekka (1992) A Systematic Approach to the Development of a Control Philosophy for the Process Industries.
[04] Junno, Seija (1989) Optimization of Steel Mill Production.
[03] Leiviskä, Kauko (1982) Short Term Production Scheduling of the Pulp Mill.
[02] Jutila, Esa (1979) Applicability of kraft cooking control models.
[01] Kiukaanniemi, Eino (1978) A systematic approach to the development task of peat fuelled heating plants.
Diploma work (M.Sc. theses)
2023
- Åman Nadja, Sensitivity analysis for multi-objective optimization weights in energy systems (Ruusunen, Ruuska & Hietaharju)
- Takalo Jeremy, Pulssikuparointilinjan toiminta sekä prosessin seurantajärjestelmän suunnittelu ja toteutus (Ruusunen, Koistinen & Sorsa)
- Moberg Jari, Vesikiertoisen lämmitysjärjestelmän kompensointimenetelmän analysointi (Ruusunen, Hietaharju & Sorsa)
- Kokkila Niklas, Data driven modelling of crystalliser particle size distribution (Ruusunen, Hietaharju & Sorsa)
- Markus Nikupeteri, Kartonkikoneen lajivaihtojen optimointi (Isokangas & Ruuska)
- Venla Huilaja, Kuorimoiden vesikierron sulkemisen haasteet ja mittausmenetelmät (Ruusunen & Isokangas)
2022
- Koivuluoma Joonas, Automated batch testing system for an optical spray combustion chamber (Ruusunen & Koistinen)
- Keronen Katja, Matalaenergiavirtojen hyödyntäminen kaukolämmön tuotannossa (Ruusunen & Hietaharju)
- Vainionpää Nanne, Risk management in large investment projects : case Metsä Fibre Oy (Ruusunen)
- Anttila Juho, Supervised nearest neighbor search in finding similar operating conditions : case: mineral processing (Ruuska, Ohenoja & Koistinen)
- Lauronen Ville, Automated PID tuning tool for HSC Chemistry Sim software (Ruuska)
- Huhtelin Sakari, Nikkelisulfaatin kriittiset ominaisuudet akkuarvoketjussa (Ruusunen)
- Sarja Henri, Mass flow estimation of granular feedstock in biorefineries (Ruusunen & Österberg)
- Niemelä Markus, Rakennusten lämpöhäviökertoimen mallinnus sisälämpötilan arvioinnissa (Ruusunen & Hietaharju)
- Pyhtilä Toni Matias, Review of selection rules for casting powders (Ruuska & Sorsa)
- Saarikettu Joni, Optimal MD Pump operation through suction liner gap control (Ruusunen, Ruuska & Koistinen)
- Simonen Konsta, Säätömenetelmien suunnittelu ja toteutus lämmitysprosessiin (Ruusunen & Sorsa)
- Pesonen Olli, Machine learning supported forecasting of baseline energy consumption for industrial processes (Ruusunen, Vuolio & Ohenoja)
- Sahi Juha, Online- ja onsite-mittaukset vedenkäsittelyprosessien seurannassa ja ohjauksessa (Ruusunen & Tomperi)
2021
- Uusitalo Pekka, Development of predictive models for catalyst development (Sorsa & Ohenoja)
- Kärkkäinen Antti, Älykäs raepuhaltamo (Ruuska & Sorsa)
- Anttila Tessa, Estimation of nitrogen oxides from a diesel engine (Ruusunen & Sorsa)
- Schroderus Jaakko, Simulation of a biorefinery concept with reliability and techno : economic assessments (Ruusunen M, Ruusunen O & Sorsa)
- Pätsi Teemu, Indirect monitoring of energy efficiency in a simulated chemical process (Ruusunen, Vuolio, Ohenoja & Österberg)
- Takkinen Veli-Matti, Lämpöpumpun lämpökertoimen ennustaminen datapohjaisella mallinnuksella (Tomperi)
- Pyhtilä Eerik, Simulation of a biorefinery concept with reliability and techno : economic assessments (Ruusunen, Ruuska, Vuokila & Hietaharju)
- Pörhö Henri, Intergration procedures of energy devices (Ruusunen, Ruuska, Vuokila & Hietaharju)
- Välikangas Henri, Real-time data quality monitoring and improvement in energy networks (Ruusunen, Ruuska, Vuokila & Hietaharju)
- Korhonen Jouko, Arinakattiloiden hyötysuhteiden vertailu eri biopolttoaineilla (Ruusunen & Österberg)
- Matturi Ville-Valtteri, New applications of optical consistency measurement (Sorsa & Ohenoja)
- Mathew Irene, Life cycle assessment of supercritical fluid extraction process (Ruusunen, Hämäläinen & Huuhtanen)
- Lahdenperä Miikka, Vesi- ja massataselaskentaohjelmat vedenkäsittelyn asiantuntijayrityksessä (Ruuska)
- Mäkimartti Oskari, Teollisuuden sivuvirtoja kestävästi hyödyntävien tuotteiden ilmastokuormanlaskentamenetelmän selvitys ja kehitys (Ruusunen)
2020
- Hämäläinen Henri, Identification and energy optimization of supercritical carbon dioxide batch extraction (Ruusunen & Österberg)
- Isometsä Juho, Kuituanalysaattorin käyttöönotto ja alustavat koeajot Heinolan flutingtehtaalla (Isokangas & Ruusunen)
- Isoaho Rasmus, Elintarviketehtaan sivutuotevirtojen optimaalinen hyödyntäminen biokaasun tuotannossa : teknis-taloudellinen tarkastelu (Ruusunen & Hietaharju)
- Laiho Olli, Valusenkan liukusulkimen säätöpiirin optimaalinen viritys (Ruuska & Sorsa)
- Naalisvaara Mikko, Comparison of control methods for simulated impurity removal in industrial wastewater treatment (Juuso)
- Laiho Olli, Valusenkan liukusulkimen säätöpiirin optimaalinen viritys (Ruuska & Sorsa)
2019
- VALTA Art, Estimation of moisture content in granular material derived from softwood (Leiviskä & Ruusunen)
- PARVIAINEN Jussi, Lämmönvaihtimien tehokkuuden seuranta ja optimointi (Ruusunen & Paavola)
- RUUSKANEN Mirja, Hienomurskaamon laaja käytettävyyden tarkastelu (Ruuska & Paavola)
- LUHTANIEMI Sini, Teräsnauhan ohjauksen mallinnus ja säätö kuumavalssaamolla (Ruuska & Sorsa)
- PULKKINEN, Jari Demand side management potential of using electric heating in Finnish buildings : current and prospective technologies (Ruusunen)
2018
- PARVIAINEN Jussi, Lämmönvaihtimien tehokkuuden seuranta ja optimointi (Ruusunen & Paavola)
- HIMANKA Ari, Minimizing pressure and consistency variations in a high-volume flow headbox (Ohenoja)
- VÄISÄNEN Mikko, Tehojouston potentiaali hajautetulla tuotannolla kaukolämpöverkossa (Ruusunen)
- VUOKILA Panu, Kysyntäjouston potentiaali maalämmössä (Ruusunen & Vuokila)
- PULKKINEN Jari, Demand Side Management potential of using electric heating in Finnish buildings – current and prospective technology (Louis, Pongrácz, Ruusunen)
2017
- RUOKANEN Olli, Häkäkaasun määrän optimointi kuumavalssaamolla. (Leiviskä, Ruuska & Sorsa)
- KIIRIKKI Kaisa, Mittausdatan ja mallien hyödyntäminen kartongin valmistuksessa. (Juuso)
2016
- KARHU Toni, Improved multi-layer printing registration control strategy for roll-to-roll printing line. (Leiviskä, Paavola & Sorsa)
- VEIJOLA Sakari, Raepuhallusprosessin optimointi. (Leiviskä & Sorsa)
2015
- TERVO Henri, Embedded bleaching controls. (Leiviskä & Sorsa)
- OIKARINEN Ville, Paperitehtaan aktiivilieteprosessin hallinta. (Leiviskä & Isokangas)
- POHJONEN Olli, Jätteenpolttolaitoksen savukaasulauhteen puhdistaminen. (Leiviskä & Sorsa)
- LAPPI Sami, A study of cleaner flotation in Aitik. (Ruuska & Malm)
2014
- COLPAERT Joakim Erik Alfred, HG-CIL feed optimization at the Raahe Laiva gold mine - . (Kuopanportti, Ruuska & Joensuu)
- JOHANSSON Sallamari Pauliina, Prosessi- ja ympäristötekniikan koulutusohjelmien ongelmakohtien kartoitus - Survey of problem points of process engineering and environmental engineering degree programs. (Jaako, Hiltunen & Heikkinen)
- KOHOLA Ville Kalervo, Kivihiiliseoksen seuranta koksaamolla - Blend tracking in the coking plant. (Leiviskä, Ruuska, Sorsa, Jalkanen, Säilyä & Ritamäki)
- KOKKONEN Antti Juhani Kalervo, Influence of Kraft recovery boiler's main control parameters on reduction degree - Soodakattilan tärkeimpien ohjaussuureiden vaikutus reduktioasteeseen. (Leiviskä, Sorsa & Ikäheimo)
- PULKKINEN Timo Juhani, Hienojakoisen kromiitin rikastaminen MGS-koepiirissä - Concentration of fine chromite in MGS test circuit. (Kuopanportti, Ruuska & Mäntylä)
- UUSI-HALLILA Senni Josefiina, Utilizing froth phase behaviour and machine vision to indicate flotation performance - . (Leiviskä, Paavola, O'Connor & Corin)
- VEIJOLA Harto Jalmari, Start-up tests of OMS's minipilot benefication plant and its applicability on the research use - Oulu Mining Schoolin minipilot-rikastuslaitteiston käyttöönotto ja sen soveltuvuus tutkimuskäyttöön. (Kuopanportti, Ruuska, Sorsa)
- RYTKÖNEN Teemu, Raaka-aineen laadun hallinta Oulun ekovoimalaitoksella. (Leiviskä & Isokangas)
- KARI Kalle, Jatkuvatoimisen hehkutusuunin energiatehokkuuden parantaminen polttoilman määrän optimoinnilla. (Leiviskä, Ruuska & Sorsa)
- HAAPALA Olli, Application software development via model based design. (Leiviskä & Sorsa)
- LAAKSO Ville, Veden ilmastuslaitteen suorituskyvyn arviointi ja optimointi. (Leiviskä & Isokangas)
2013
- HIETAHARJU Petri Juhani, Veden hapetuslaitteen prototyypin toimintaperiaatteen todentaminen ja hapetustehon määrittäminen - Testing of an aeration device prototype to confirm its operating principle and oxygentransfer capabilities. (Leiviskä & Isokangas)
- KALAOJA Mikko Johannes, Koivun rumpukuorintaan vaikuttavat tekijät talvella - Parameters affecting birch drum debarking in winter. (Isokangas & Söderling)
- KAUPPI Tomi-Petri Mikael, JT-rikastamon hienopiirin prosessin hallinta ja lietteen käsittelyn kehittäminen - Control of fine material circuit of the JT-valorization plant and development of sludge handling. (Leiviskä, Ruuska, Sorsa & Nikola-Määttä)
- KORHONEN Juha Tuomas, Online-mittauksien hyödyntäminen puhdistetun yhdyskuntajäteveden bakteerimäärien arvioinnissa - Utilization of on-line measurements in estimation of bacterial amounts in purified municipal wastewater. (Rämö & Juuso)
- LAUKKA Arto Jaakko, Pyriittituotannon kehittäminen Pyhäsalmen kaivoksen rikastamolla - Development of pyrite production in Pyhäsalmi mine mill. (Yliniemi, Ruuska & Pekkala)
- MANKINEN Antti Heikki Sakari, Sotkamon hopekaivoksen hopea-pyriittirikasteen kaupallinen hyödyntäminen - Commercial benefication of silve-pyrite concentrate of Sotkamo Silver Mine. (Kuopanportti, Ruuska, Pietilä & Kovalainen)
- OLLAKKA (Karppinen) Henna Kristiina, Monimuuttuja-analyysi Talvivaaran bioliuotuskasoille - Multivariate analysis for Talvivaara Mine's bioleaching heaps. (Taskila, Ruuska, Pöllänen & Palmu)
- TAKALA Tuomas Kari, Jatkuvatoimisten mittausten merkitys talteenottolinjan hallinnassa - The effect of continuous on-line measurements in the control of chemical recovery plant. (Leiviskä, Koskinen & Ikäheimo)
2012
- HYVÖNEN Jari Petteri, ~ - Real-time determination of metal concentrations in liquids using micro-plasma emission spectroscopy. (Leiviskä & Laurila)
- KARJALAINEN Jenni Maija Annikki, Yksikkötestaus Simulinkissä - Unit testing in Simulink. (Leiviskä & Saikkonen)
- KOSAMO Jarno Tapio, Levyvalssaimen työvalssien profiilin mallintaminen - Modeling the profile of plate mill work rolls. (Leiviskä, Paavola & Rautiainen)
- LOUIS Jean-Nicolas, ~ - Smart buildings to improve energy efficiency in the residential sector. (Pongrácz, Caló, Juuso & Sörensen)
- TIKKA Johanna Emilia, Sulfidirikasteen laadun parantaminen - Improving the quality of sulphide concentrate. (Fabritius, Ruuska, Mörsky & Roimaa)
- SEPPÄLÄ Pirjo Sanna Marita, Tietoliikenne- ja -järjestelmäratkaisut Kemin kaivoksen tiedonhallinnassa - Communications and data system solutions in the Kemi mine information management. (Leiviskä, Paavola & Salmi)
- SILLANPÄÄ Elena Anna Mari, Kemin kaivoksen liikkuvan kaluston ajoneuvopäätteiltä saatavan tiedon hyödyntäminen - Utilizing the information from vehicle displays at Kemi mine. (Leiviskä & Salmi)
- VARPE Eva-Leena Kristiina, Tasokohtaisen poisto-ilmanohjaus Kemin kaivoksella - Level based exhaust air control in Kemi Mine. (Leiviskä, Näsi & Salmi)
2011
- HANSEN-HAUG Tommi, Alkali chloride measure-ment application in a varying fuel fired CFB boiler (Leiviskä, Ruusunen, Kemppainen)
- HONKONEN Jouni Sakari, Masuunin panostus 100 % pellettiajolla - Blast furnace charging with 100% pellet burden. (Leiviskä, Paananen, Ruuska)
- KONTTILA Sakari, Kalkinpolttoprosessin vaikutus poltetun kalkin laatuun - The influence of calcination process on the quality of quicklime (Leiviskä, Ruuska, Kerkkonen)
- KOSKENKORVA Juha, Puun käsittelyn toimintojen kehittäminen - The development of the woodhandling (Leiviskä, Isokangas, Luukkainen, Ruonala)
2010
- ARFFMAN Matti, Vedenpuhdistusprosessin kehittäminen mallinnuksen avulla - Development of the water purification process with modelling methods
- KARJALAHTI Jukka, Improving fault detection performance and energy efficiency of a wireless vibration analysis system
- KOSKENNIEMI Anssi, Differentiaalievoluutio ja geneettiset algoritmit epälineaaristen prosessimallien identifioinnissa - Differential evolution and genetic algorithms in the identification of nonlinear process models
- MAUNUKSELA Kati, Sekoitusmenetelmän optimointi metrologisessa tuulitunnelissa - Optimizing mixing method in metrological wind tunnel
- PASMA Katja, Lohkaremyllyn ajotavan kehittäminen
- PASMA Mira, Paperiradan poikkiprofiilien vaikutus paperikoneen energiatehokkuuteen - Effects of CD profiles on paper machine's energy efficiency
- REIJONEN Hanna, Tiedonlouhinta navettatietojärjestelmäaineistojen tutkimisessa - Data mining in data bases of cow barns
- SAARINEN Timo, Energiatehokkuusjärjestelmän raportointi ja mittarointi - Reporting and measurements in a energy efficiency system
- TAPIO Karoliina, Paperitehtaan jätevesilaitoksen toiminnan optimointi - Optimization of the operation of paper mill wastewater treatment plant
- TUIKKA Henri, Energianhallintajärjestelmä ja tuotannon optimointi sähkön ja lämmön yhteistuotannossa - Energy management system and production optimization in combined heat and power production
- UUSITALO Jani, Polttokennoprosessin mallinnus ja simulointi - Modelling and simulation of fuel cell process
- VEIJOLA Ilmari, - Optimization model for ammonium sulfate production in a coke oven byproduct plant
- VIRTANEN Erkki, Koksaamon johtamisen tietojärjestelmän määrittely - Management information system specification of coking plant
2009
- HAKA Jani, Aktiivilietelaitoksen mittaustiedon analysointi. - Analysis of activated sludge process measurement data.(Leiviskä)
- HEINONEN Petri, Sumea asiantuntijajärjestelmä ja GA optimointi ravintolaskentasovelluksessa. - Fuzzy expert system and GA optimization in dietary guidance application. (Juuso, Sorsa)
- KIUTTU Jarmo, Jauhatus- ja vaahdotusprosessin koulutussimulaattorin kehittäminen. - Development of the training simulator for grinding and flotation. (Leiviskä)
- KORHONEN Jarkko, Ohutseinämäisten polypropeenituotteiden laadunvalvonnan parantaminen ruiskuvalu-prosessissa. - Improving quality control for thin-walled polypropylene products in injection molding process.(Leiviskä)
- LAMMI Petri, Lainerin käyryyden hallinta. - Curl control in liner production. (Leiviskä)
- LAUNONEN Frans, Pienimittakaavaisten pellettipolttimien polttoprosessin identifiointi ja säätö. - Process identification and combustion control of small-scale pellet burners – a data-based modelling approach. (Leiviskä, Ruusunen)
- LINDROTH Jori, Geologisten näytteiden esikäsittelyn automaatio. - Automation of geological sample preparation.(Yliniemi)
- NIKULA Riku-Pekka, ~ - A wireless approach to data stream mining-based pump diagnosis. (Leiviskä)
- PALMUJOKI Matias, Sylinteripaineanturin mittasignaalin simulointi kipinäsytytteisessä kaasumoottorissa. -Simulation of cylinder pressure sensor signals from a spark ignited gas engine. (Leiviskä)
- PARVIAINEN Juha, Maaperän luokittelu MLP-neuroverkko- ja painoarvomenetelmillä. - Soil classification using MLP neural network and Weights of Evidence methods. (Leiviskä)
- SAARELA Ville, Kehittynyt säätöratkaisu vetykäsittelyprosessin tuotannon tehostamiseen ja rajoitteiden kartoitukseen. - Advanced control structure for production intensification and constraint analysis in hydrotreating process. (Leiviskä)
2008
- AARNIO Janne, Kuumavalssatun teräslevyn muototarkkuuden kehittäminen. - Development of the shape accuracy for hot plate rolling.
- ARPOLA Tiina, Fermentoinnin jatkuvatoiminen monitorointi. - Continuous monitoring of fermentation.
- HOLCK Päivi, Parametrien identifiointi geneettisillä algoritmeilla biologiselle jätevedenkäsittelyprosessille. - Parameter identification with genetic algorithms for bioloqical wastewater treatment process.
- KALLIJÄRVI Atte, Klooridioksidiprosessin hyötysuhteen mallintaminen ja monimuuttujasäätöjen simulointi -Multivariable control simulation and efficiency modelling in the chlorine dioxide process.
- KAUPPI Marjo, Automaatiota hyödyntävän 3D-kokonaistoimintaprosessin kehittäminen pilaristabilointiin. -Development of automated 3D operating process for column stabilisation.
- KEMPPAINEN Juha, ~ - Wireless sensor network in process automation.
- KESKITALO Jukka, Sellu- ja paperitehtaiden jätevesiä käsittelevän aktiivilieteprosessin datapohjainen mallintaminen. - Data based modelling of activated sludge process treating pulp and paper mill wastewater.
- KREULA Jussi, Sähkön kulutuksen etämittauksen hyödyntäminen asiakasryhmäkohtaisen kulutusprofiilin määrittämisessä. - Exploiting electricity consumption measurement data in specifying real consumption of the customer groups.
- OHENOJA Markku, Etanolin refomoinnin mallinnus ja simulointi. - Modelling and simulation of ethanol refoming.
- RAATIKAINEN Mika, Pesulatietojärjestelmien tiedonlouhinta laskennallisilla menetelmillä CASE: huollettavien sairaalatekstiilien kiertonopeuden tutkiminen. - Data mining using computational intelligence in laundry information system CASE: Turnover exploration of service hospital textiles.
- TERVAHARTIALA Pasi, Valmistusprosessien tilastollinen monitorointi. - Statistical monitoring of manufacturing process.
- TOLONEN Teppo, Saostumaperäisten katkojen syiden selvittäminen ja analysointi. Root cause analysis of precipitate-based web breaks.
- VAARA Juho, Energiatehokkuus puristinosalla. - Energy efficiency in press section.
2007
- 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 valmistuksessa. - 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 tuotantoyksikössä - 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 prosessinohjaus. - 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 pintavikojen vähentäminen. - Quality development of coated paper.
- Skön Jukka-Pekka, Laskennallisten menetelmien soveltaminen QSAR-analyysissä, case: Yhdisteiden karsinogeenisuuden mallintaminen neuroverkoilla. - Using computational methods in QSAR analysis, case: modelling compound carsinogenicity using the neural networks.
- Vähäkangas Ville, - - Artical immune systems in fault diagnosis.
2006
- HUHMARNIEMI Tuomas, - Examination of adaptive Fuzzy PI-type controllers.
- KERÄNEN Seppo, Jatkuvatoimisen kosteusmittausanalysaattorin tarkkuuden parantaminen sekä mittauksen kytkeminen säätöön. - Improving the accuracy of an on-line moisture analyser and including the measurement in control
- LAHMA Santtu, Vianilmaisujärjestelmän hyödyntäminen paperitehtaalla. - Utilizing a web imaging system in a paper machine.
- LEHIKOINEN Lotta, Juusto- ja heratuotannon orgaanisen jätevesikuormituksen selvittäminen, Case Study Valio Oy, Haapavesi - Research of organic waste water loading caused by cheese and whey production. Case Study Valio Oy Haapavesi.
- LÄMSÄ Jaakko, Esiselvitys höyryreformointiyksikön tietokonesäädöistä. - Prestudy for advanced control of a steam reforming unit.
- MIKKONEN Tommi, Paperinvalmistuslinjan käyttökokemustiedon keruu ja analyysi. - Collection and analysis of operating experience data in paper production line.
- MÄYRÄ Outi, Luonnollinen levenemä kuumanauhavalssauksessa. - Natural spread in finishing mill.
- PIHTSALMI Laura, Puun ominaisuuksien ja kapasiteetin vaikutus hakkeen laatuun. - Influence of wood characteristics and capacity on the quality of wood chips.
- PORKOLA Sami, Kuorimon puuhäviön ja hakepuhtauden analyysi. - The analysis of wood losses and log cleanliness in a debarking plant.
- POTTALA Jaakko, Kuumavalssatun kohokuvioidun teräsnauhan valmistus. - Manufacturing of hot rolled patterned steel strip.
- PYYKKÖNEN Janne, Keittimen toiminnan parantaminen toimintapisteen muuttuessa. - Improving digester functionality in a new operation point.
- RÄISÄNEN Jukka, Viirakaivon varaustilasäädön toteuttaminen. - Implementation of charge control of white water.
- SALMELA Janne, Pelletin laatuun vaikuttavat tekijät. - Factors influencing pellet quality.
- SIRVIÖ Jukka-Pekka, Laboratoriomittakaavaisen laskeutuslaitteiston kehitys ja scaleup menetelmät. - Development of a laboratory scale sedimentation device and its scale-up methods.
- VASANKARI Heini, Kuituanalysaattorin käyttö sellutehtaan laadun valvontaan ja prosessin hallintaan. - The use of a fiber analyzer for the quality and process monitoring in a pulp mill.
2005
- ANTTILA Esa, - Optimization of Bending Done With Coilbox
- HAAPALAINEN Risto, - Factors That Effect Coke Pushing Intensity
- HYTTINEN Matti, - Studying of Coating Uniformity with Different Measuring Techniques
- HÄNNINEN Antti, - Development of an Alloying Calculation Model for Ladle Treatment
- KYLLÖNEN Toni, - Oxygen/Inert Ratio Control at Step 4 in AOD-process
- PIETILÄ Jari, - The Ultilization of On-line Beating Degree Analyzer in the Refining Control of the Fine Paper Machine
- PIETILÄ Kai, - Identification and Control of Batch Combustion of Wood in a Fireplace
- RAHKOLIN Vesa, - Analysis and Modelling of the Final Clarification of the Wastewater Treatment Plant
- SIRKKA Jouni, - Real-time Process Control Via Network
- TAPIO Heidi, - Rationalizing the Implementation of the Optimization Products
- TENKKU Heikki, - Measuring the Moisture in Chromite Concentrate Using Microwave Technique
2004
- Hayles Charles, - Combustion of mixed-fuel: review and survey of Finnish plants
- Heiskanen Janne, Kivihiiliseoksen laadullisten muuttujien vaikutukset koksipainoon - Influence of qualitative variables of coal blend on cokeweight
- Helisten Riikka, - The applicability of near-infrared techniques for measuring the moisture of sinter mix
- Laitinen Jussi, - Algorithms for multivariate calibration
- Lampela Janne, - Developing the slab quality prediction model by inserting new factors
- Pahkala Pasi, - Measurement or refractory lining in 150-ton AOD converter
- Penttilä Mika, - Test system interface for production line control and monitoring
- Sipilä Juha, - Optimisation of scrap charge of converter
- Sorsa Aki, Älykkäiden säätimien kehitys ja viritys vedenpuhdistuskemikaalien annosteluun - The development and tuning of the intelligent controllers for wastewater purification chemicals dosage
- Uusikartano Antti, Kromikonvertterin ajotavan ja laskentamallin kehittäminen- Development of CRC-process and calculation
- Vähänikkilä Satu, Steckel-valssaimen uunikelaimen vedon ohjaus - Furnace coiler tension control in Steckel mill
2003
- Harinen Antti, Kiintoainemittauksen sovelluskohteet yhdyskuntajäteveden puhdistuksessa - Applications of total solids measurement in municipal wastewater treatment
- Kela Jarmo, Autoklaavireaktorin säätö - Control of autoclave reactor
- Koivisto Antti, Hierrelinjan massamäärän ennusteen luotettavuuden arviointi - Reliability of pulp yield prediction estimate for TMP-line
- Nauha Matti, Läpilyöntiuunin kuumennuksen optimointi - Heating optimization of the pusher type furnace
- Peltonen Janne, Kattilalaitoksen turvallisuuteen liittyvän järjestelmän toteutus ohjelmoitavilla laitteilla -Implementation of safety-related system of boiler plant with programmable systems
- Pirttimaa Mika, - Solder paste printing statistical process control of the printing quality
- Tissari Soile, Maalajien luokittelu painoarvomenetelmää ja RBFLN-neuroverkkoa käyttäen - Classification of surfacial soil deposits using Weights-of-Evidence-method and RBFLN-neural nets
2002
- Ahvenlampi Juha, Meesasuotimen optimoivat säädöt - Lime mud filter optimising controls
- Joensuu Pasi, Koksin kuivasammutuksen simulointi - Simulation of coke dry quenching
- Kivelä Jani, Valkaisuprosessin optimointi sekä hönkäkaasun happimittauksen soveltuvuus hiokkeen peroksivalkaisun säätöön - Optimization of bleaching process and applicability of exhaust gas oxygen analyzer in control of peroxide bleaching of groundwood
- Kolari Sari, - Development and production of coater specific troubleshooting tools
- Korhonen Aki, Hake- ja massavirtauksen säätäminen jatkuvassa keitossa - Control of chip and pulp flow in continuous digester
- Kumpula Henri, - HOC simulator as a tool on paper machine service
- Laitinen Ossi, Mekaanisten massojen kuitujakeiden ja hienoaineen määritys fraktionaattorilla - Determination of mechanical pulp fibre and fines fractions with a fractionator
- Leiviskä Marko, - IT & Forest Industry Consulting
- Lähdemäki Riku, - The effect of malfunctional partial process on production
- Mecklin Mika, - Chemical balance analysis of recovery line
- Paavola Marko, - Development of a Diagnostic System for Manufacturing Equipment
- Posio Jani, Mekaanisen massan HC-peroksivalkaisun säädön kehittämiseen - Development of control system for HC-peroxide bleaching of mechanical pulp
- Pöllänen Kati, - Process Control Analysis Requirements in a Cold Rolling Mill
- Rentola Ismo, - The effect of chemical factors and casting machine�s condition on surface cracks forming in a steel slab
- Saarela Antti, Masuunin raudanlaskujen asiantuntijajärjestelmän sulkutapahtumamodulli - Taphole plugging rule-base module for blast furnace iron tapping expert system
- Saarela Ulla, Fed-batch entsyymifermentointiprosessin mallinnus - Modelling of a bed-batch entzyme fermentation process
- Vuononvirta Reeta, Päällystetyn hienopaperin picking- ja muihin pintalujuusominaisuuksiin vaikuttavien tekijöiden selvitys - Factors affecting picking and surface strength properties in coated wood paper
- Ypyä Olli, Päällystyskoneen ylösajoprofiilin hallinta - Co-ordinated Start up Profiles at the Off-machine Coater
2001
- Hakala Outi, - Automatic shape optimisation combination with CFD modelling
- Kangas Pekka, Prosessin stabiilisuuden vaikutus paperin laatuun - The influence of the Process Stability on the Paper Quality
- Kinnunen Kimmo, Sintrausseoksen kaasunläpäisevyyden hallinta kosteuden avulla - Management of the sintering mix permeability by moisture control
- Koskinen Jyrki, Hierreprosessin hallinta - Control system of TMP Process
- Laukkanen Timo, Hiomakiven terävyyden hallinta asiantuntijajärjestelmällä - Pulp Stone Sharpness Control by an Expert System
- Penttinen Sasu, Paperikoneen katkoherkkyysindikaattorin on-line-testaus - On-line testing of the web break sensitivity indicator for a paper machine
- Riihimäki Hannele, Aktiivinen raportointi toteutettuna XML:n avulla - Active Reporting with XML
- Ruusunen Mika, Pienimittakaavaisen puun polttoprosessin identifiointi - Identification of small-scale Wood Combustion
- Saloranta Antti, Tietokantojen käyttö hajautetun Java-ympäristön toteutuksessa- The use of databases in the implementation of decentralized Java-environment
- Sivonen Jukka, Propulsiosäädön testausmenetelmät - Propulsion control test methods
- Tantarimäki Juha, LoopBrowser asiakaspalvelutuotteena - LoopBrowser as a service product
- Tuhkanen Henna, Kuivapainomittauksen käyttö päällystyskoneen päällystemääräprofiilin säädössä - Coat Weight Profile Control in a Coating Machine Using Internet
- Viinikainen Petri, Internet-avaintenvaihtoprotokollan käytettävyys mobiilin internetin sovelluksissa ja kommunikaatiossa - Key Exchange Protocol Usability in Mobile Internet Applications and Communications
- Virtanen Visa, Teräksen pinnan integraatioedut suunnittelujärjestelmässä - Surface inspection of steel using Self-Organizing Maps
- Ylikunnari Jukka, Liuottajan säätö - Control of smelt dissolving tank
2000
- Alatalo Sanna, Levylinjan lämpötilan hallinta - The temperature control of a plate mill
- Haapalainen Jukka, - Built-in quality control in JOT modules
- Isokangas Ari, Rumpukuorinnan puuhäviöiden mallintaminen ja optimointi - Modelling and optimising wood losses of drum debarking
- Jokinen Timo, Elektroniikkatuotteen laadunennustustyökalun käyttöliittymä - Quality Forecasting Tool user interface for electronics manufacturing
- Kaasila Marko, Raudanlaskujen hallinnan asiantuntijajärjestelmän rakenteen määritys - Modular structure of expert system for controlling iron tapping
- Keinänen Pasi, Erään sellutehtaan ECF-valkaisun pesujen, vesikiertojen ja toiminnan kehittämismahdollisuuksin tarkastelu - Finding ways to develop the washing, water circulations and operation of an ECF bleaching process
- Kivelä Satu, Konvertteriprosessin hiilipitoisuuden hallinta sumealla säädöllä - Control of the carbon content of the BOS by fuzzy control
- Kumara Timo, WIC 100 datan hyödyntäminen paperitehtaan märkäosan prosessin säädössä - The use of WIC 100 data in paper mill wet end process control
- Lehmus Maija, Kuivauskoneen käyttö- ja laaturaportointi nykyaikaisessa sellutehtaassa - Operation and quality reporting of a drying machine in the modern pulp mill
- Niemelä Tanja, Informaatiojärjestelmän tehokas käyttö tuotannonohjauksessa - Efficient use of the information system in production control
- Niiranen Marko, Menetelmä tietokoneen suorituskyvyn määrittämiseen ja sen soveltaminen hajautetun verkonvalvonnan optimointiin - A method for estimating the general performance of a computer and an application to distributed network monitoring system
- Peltonen Teemu, Määrähyötysuhteeseen vaikuttavien tekijöiden kartoitus ja optimointi taidepainopaperilinjassa -Charting and optimising the factors influencing material efficiency in art quality producing paper machine line
- Poutilainen Jussi, Läpipalamisen hallinta sintrauskoneella sumealla nopeudensäädöllä - Burn-through management in sintering machine by fuzzy speed control
- Puurunen Mika, Hälytysten luokittelu geneerisessä vikadiagnostiikka-arkkitehtuurissa - Alarms classification in a generic fault diagnostic architecture
- Söderström Satu, Sellun lujuusominaisuuksien spektroskopinen karakterisointi - Spectroscopic characterisation of pulp strength properties
- Uusipaavalniemi Jussi, Sääntöpohjaisen asiantuntijajärjestelmäsäätimen kehitys - Development of a rule based expert system controller
- Uusitalo Mikko, Kartongin päällysteen kuivatuksen optimointi - The optimal drying strategy for coated paperboard
- Viirret Katja, Älykkäät menetelmät jäteveden puhdistuskemikaalien annostelun säädössä - Intelligent methods in the dosing control of wastewater purification chemicals
- Voutilainen Jussi, Raudanlaskujen asiantuntijajärjestelmään liittyvien mittausten arviointi - Evaluation of measurements associating iron tapping expert system
Courses
Control Engineering group provides high level teaching of master and doctoral level students based on its research fields.
- basics of control and instrumentation
- modelling
- simulation
- optimisation
- intelligent methods
477051A Automaatiotekniikka / Automation engineering
https://opas.peppi.oulu.fi/en/course/477051A/5605
488051A AutoCAD ja Matlab prosessi- ja ympäristötekniikan työkaluna / AutoCAD and Matlab in Process and Environmental Engineering
https://opas.peppi.oulu.fi/en/course/488051A/5628
477502A Koesuunnittelu ja kokeellisen datan analysointi / Experiment design and analysis
https://opas.peppi.oulu.fi/en/course/477502A/2510
477501A Prosessidynamiikka / Process dynamics
https://opas.peppi.oulu.fi/en/course/477501A/2509
477509S Datapohjainen mallinnus / Data-driven modellling
https://opas.peppi.oulu.fi/en/course/477509S/16755
477524S Prosessien optimointi / Process optimization
https://opas.peppi.oulu.fi/en/course/477524S/5619
477525S Älykkäät laskennalliset menetelmät automaatiossa
https://opas.peppi.oulu.fi/en/course/477525S/5620
477506S Modelling and control of biotechnical processes
https://opas.peppi.oulu.fi/en/course/477506S/2514
477523S Simulointi / Simulation
https://opas.peppi.oulu.fi/en/course/477523S/5618
477510S Rikastusteknisten prosessien mallinnus / Automation in Mineral Processing
https://opas.peppi.oulu.fi/en/course/477713S/4276
477508S Automation in metallurgical industry