| Wireless sensor networks in industrial automation M Paavola, K Leiviska Factory Automation, 2010 | 73 | 2010 |
| Continuous direct tablet compression: effects of impeller rotation rate, total feed rate and drug content on the tablet properties and drug release MA Järvinen, J Paaso, M Paavola, K Leiviskä, M Juuti, F Muzzio, ... Drug development and industrial pharmacy 39 (11), 1802-1808, 2013 | 65 | 2013 |
| Functionality of turbidity measurement under changing water quality and environmental conditions J Tomperi, A Isokangas, T Tuuttila, M Paavola Environmental technology 43 (7), 1093-1101, 2022 | 59 | 2022 |
| Comparison of a continuous ring layer wet granulation process with batch high shear and fluidized bed granulation processes MA Järvinen, M Paavola, S Poutiainen, P Itkonen, V Pasanen, K Uljas, ... Powder Technology 275, 113-120, 2015 | 37 | 2015 |
| Modeling continuous high-shear wet granulation with DEM-PB T Kulju, M Paavola, H Spittka, RL Keiski, E Juuso, K Leiviskä, E Muurinen Chemical Engineering Science 142, 190-200, 2016 | 31 | 2016 |
| Wireless technologies in process automation: a review and an application example M Paavola University of Oulu, 2008 | 24 | 2008 |
| Development and calibration of a dynamic flotation circuit model P Seppälä, A Sorsa, M Paavola, J Ruuska, A Remes, H Kumar, ... Minerals Engineering 96, 168-176, 2016 | 18 | 2016 |
| Towards online adaptation of digital twins RP Nikula, M Paavola, M Ruusunen, J Keski-Rahkonen Open Engineering 10 (1), 776-783, 2020 | 16 | 2020 |
| Pilot plant simulation as a tool for more efficient mineral processing P Seppälä, A Sorsa, M Paavola, A Remes, J Ruuska, K Leiviskä IFAC Proceedings Volumes 47 (3), 11506-11511, 2014 | 9 | 2014 |
| 3D population balance model for continuous twin screw granulator MEA Paavola, A El Hagrasy, J Litster, K Leiviska Chemical Engineering Transactions 32, 2077-2082, 2013 | 9 | 2013 |
| An efficient entropy estimation approach M Paavola University of Oulu, 2011 | 9 | 2011 |
| Wireless monitoring of a steam boiler-performance measurements in industrial environment M Paavola, J Kemppainen 2008 IEEE International Symposium on Industrial Electronics, 1166-1171, 2008 | 8 | 2008 |
| Process control in intensified continuous solids handling M Ohenoja, K Boodhoo, D Reay, M Paavola, K Leiviskä Chemical Engineering and Processing-Process Intensification 131, 59-69, 2018 | 7 | 2018 |
| Comparison of three change detection algorithms for an electronics manufacturing process M Ruusunen, M Paavola, M Pirttimaa, K Leiviska 2005 International Symposium on Computational Intelligence in Robotics and …, 2005 | 7 | 2005 |
| Towards mineral beneficiation process chain intensification M Ohenoja, M Ruusunen, A Koistinen, J Kaartinen, J Paaso, A Isokangas, ... IFAC-PapersOnLine 51 (21), 201-206, 2018 | 6 | 2018 |
| Quality monitoring and fault detection in an automated manufacturing system: a soft computing approach M Ruusunen, M Paavola University of Oulu, 2004 | 6 | 2004 |
| Golden AI data acquisition and processing platform for safe, sustainable and cost-efficient mining operations J Havisto, T Matselyukh, M Paavola, S Uusitalo, M Savolainen, ... 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 5775 …, 2021 | 5 | 2021 |
| Wireless networks in underground mines M Paavola, P Seppälä Industrial Wireless Sensor Networks: Monitoring, Control and Automation, 2015 | 5 | 2015 |
| Some change detection and time-series forecasting algorithms for an electronics manufacturing process M Paavola, M Ruusunen, M Pirttimaa University of Oulu, 2005 | 5 | 2005 |
| Predictive optimization of the heat demand in buildings at the city level P Hietaharju, M Ruusunen, K Leiviskä, M Paavola Applied Sciences 9 (10), 1994, 2019 | 4 | 2019 |
