{"id":null,"code":"TP00AQ18","name":{"valueFi":"Mallinnus ja säätö teollisten prosessien hallinnassa","valueEn":"Modelling and control for industrial processes","valueSv":""},"credits":10.0,"minCredits":5,"maxCredits":10,"tags":[],"createdAt":1790534854393,"contentList":[{"title":{"valueFi":"Osaamistavoitteet","valueEn":"Learning outcomes","valueSv":""},"content":{"valueFi":"Module 1: Methods and tools  \r\nAfter module 1, students understand the main concepts of modelling, control and optimization methodology behind the applications and can use Simulink and other tools adequately to pass the course.  \r\n\r\nModule 2: Bio-technical processes  \r\nAfter module 2, students can model kinetics and dynamics of bio-technical processes (mainly fermentation) starting from the process phenomena and mass balance models. They understand the limitations of different modelling approaches and assumptions, and fundamentals of monitoring and optimization of bioprocesses with respect to energy, economic, and environmental issues. Students have preliminary skills to develop models in Matlab/Simulink environment. \r\n\r\nModule 3: Metallurgical processes\r\nAfter module 3, students understand the management and control problems in metallurgical industry and can choose between the main modelling and control methods to solve them. They can analyse the control of separate processes and larger process lines and can estimate technical and economic effects of automation in metallurgical industry. \r\n\r\nModule 4: Minerals processing\r\nAfter module 4 students have the skills to understand and develop mathematical models for minerals processing and apply these models in process monitoring, optimization and control applications. Students can recognize the primary physical and chemical phenomena related to the material and energy balances of the (selected) processes. Students can link the control variables, manipulated variables and disturbance variables to the models. Students can differentiate the basic and advanced level controls and are familiar with applications of machine learning and novel monitoring in mineral processing.","valueEn":"Module 1: Methods and tools  \r\nAfter module 1, students understand the main concepts of modelling, control and optimization methodology behind the applications and can use Simulink and other tools adequately to pass the course.  \r\n\r\nModule 2: Bio-technical processes  \r\nAfter module 2, students can model kinetics and dynamics of bio-technical processes (mainly fermentation) starting from the process phenomena and mass balance models. They understand the limitations of different modelling approaches and assumptions, and fundamentals of monitoring and optimization of bioprocesses with respect to energy, economic, and environmental issues. Students have preliminary skills to develop models in Matlab/Simulink environment. \r\n\r\nModule 3: Metallurgical processes\r\nAfter module 3, students understand the management and control problems in metallurgical industry and can choose between the main modelling and control methods to solve them. They can analyse the control of separate processes and larger process lines and can estimate technical and economic effects of automation in metallurgical industry. \r\n\r\nModule 4: Minerals processing\r\nAfter module 4 students have the skills to understand and develop mathematical models for minerals processing and apply these models in process monitoring, optimization and control applications. Students can recognize the primary physical and chemical phenomena related to the material and energy balances of the (selected) processes. Students can link the control variables, manipulated variables and disturbance variables to the models. Students can differentiate the basic and advanced level controls and are familiar with applications of machine learning and novel monitoring in mineral processing.","valueSv":""}},{"title":{"valueFi":"Sisältö","valueEn":"Content","valueSv":""},"content":{"valueFi":"Module 1: Methods and tools \r\nRecap of data-based modelling, process dynamics and optimization methods. Simulink. Other methods and tools.\r\n\r\nModule 2: Bio-technical processes\r\nBioreactors: models, kinetics and transfer phenomena. Models: different modelling approaches with examples. Measurements and control aspects in fermentation processes. Implementation of a bioreactor model with Matlab/Simulink. \r\n\r\nModule 3: Metallurgical processes\r\nModelling and control examples of steel production processes: coking, sintering, blast furnace, steel converter, continuous casting, and rolling mill. Model solutions by special-purpose simulators. Also some special measurements are introduced.\r\n\r\nModule 4: Mineral processing\r\nMathematical (mechanistic and data-driven) models for processes such as crushing, grinding, flotation, leaching, separation. Examples how to use these models in process design and automation related problems and what kind of benefits can be drawn from their use.","valueEn":"Module 1: Methods and tools \r\nRecap of data-based modelling, process dynamics and optimization methods. Simulink. Other methods and tools.\r\n\r\nModule 2: Bio-technical processes\r\nBioreactors: models, kinetics and transfer phenomena. Models: different modelling approaches with examples. Measurements and control aspects in fermentation processes. Implementation of a bioreactor model with Matlab/Simulink. \r\n\r\nModule 3: Metallurgical processes\r\nModelling and control examples of steel production processes: coking, sintering, blast furnace, steel converter, continuous casting, and rolling mill. Model solutions by special-purpose simulators. Also some special measurements are introduced.\r\n\r\nModule 4: Mineral processing\r\nMathematical (mechanistic and data-driven) models for processes such as crushing, grinding, flotation, leaching, separation. Examples how to use these models in process design and automation related problems and what kind of benefits can be drawn from their use.","valueSv":""}},{"title":{"valueFi":"Suoritustavat","valueEn":"Study Methods","valueSv":""},"content":{"valueFi":"Various types of individual and group assignments. \r\n5 ETCS is given if a student passes Module 1 and one of modules 2-4. \r\n10 ECTS is given if a student passes all the modules.\r\n\r\nThe course completion methods develop: \r\n- Analytical, critical and creative thinking skills (analysis and separation of information from the essential, examination of methods, sources and research results, drawing conclusions, problem identification, source criticism)  \r\n- International and multicultural skills (openness, curiosity, courage, flexibility and patience in multicultural contexts) \r\n- Multidisciplinary and interdisciplinary skills (combining and utilising expertise from different fields, appreciating and accepting different fields and perspectives)\r\n- Well-being self-development skills (time management, self-management)\r\n- Communication, interaction and digital skills (clear and concise expression, listening and discussion skills, cooperation and teamwork skills)","valueEn":"Various types of individual and group assignments. \r\n5 ETCS is given if a student passes Module 1 and one of modules 2-4. \r\n10 ECTS is given if a student passes all the modules.\r\n\r\nThe course completion methods develop: \r\n- Analytical, critical and creative thinking skills (analysis and separation of information from the essential, examination of methods, sources and research results, drawing conclusions, problem identification, source criticism)  \r\n- International and multicultural skills (openness, curiosity, courage, flexibility and patience in multicultural contexts) \r\n- Multidisciplinary and interdisciplinary skills (combining and utilising expertise from different fields, appreciating and accepting different fields and perspectives)\r\n- Well-being self-development skills (time management, self-management)\r\n- Communication, interaction and digital skills (clear and concise expression, listening and discussion skills, cooperation and teamwork skills)","valueSv":""}},{"title":{"valueFi":"Toteutustavat","valueEn":"Teaching Methods","valueSv":""},"content":{"valueFi":"Hybrid\r\nDistance and face-to-face teaching    \r\nSummer: Self-paced","valueEn":"Hybrid\r\nDistance and face-to-face teaching    \r\nSummer: Self-paced","valueSv":""}},{"title":{"valueFi":"Oppimateriaalit","valueEn":"Learning material","valueSv":""},"content":{"valueFi":"<p>Lecture notes, other material distributed during the lectures, other literature.</p>","valueEn":"<p>Lecture notes, other material distributed during the lectures, other literature.</p>","valueSv":""}},{"title":{"valueFi":"Lisätiedot","valueEn":"Further information","valueSv":""},"content":{"valueFi":"Language of instruction: English\r\nTiming: Periods 1 and 2\r\nTarget group: M.Sc. students of Process and Environmental Engineering\r\nPersons responsible for the course: Aki Sorsa and Mika Ruusunen \r\nPersons responsible for the modules:  \r\nModule 1: Aki Sorsa\r\nModule 2: Mika Ruusunen \r\nModule 3: Jari Ruuska \r\nModule 4: Markku Ohenoja","valueEn":"Language of instruction: English\r\nTiming: Periods 1 and 2\r\nTarget group: M.Sc. students of Process and Environmental Engineering\r\nPersons responsible for the course: Aki Sorsa and Mika Ruusunen \r\nPersons responsible for the modules:  \r\nModule 1: Aki Sorsa\r\nModule 2: Mika Ruusunen \r\nModule 3: Jari Ruuska \r\nModule 4: Markku Ohenoja","valueSv":""}},{"title":{"valueFi":"Kurssikirjallisuus","valueEn":"Literature","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Esitietovaatimukset","valueEn":"Qualifications","valueSv":""},"content":{"valueFi":"No course requirements. Knowledge of data analysis, data-based modelling, process dynamics and process optimization promote learning. Mathematics or the methodology is not specifically taught during the course and thus, if needed, students must independently obtain the knowledge needed.","valueEn":"No course requirements. Knowledge of data analysis, data-based modelling, process dynamics and process optimization promote learning. Mathematics or the methodology is not specifically taught during the course and thus, if needed, students must independently obtain the knowledge needed.","valueSv":""}},{"title":{"valueFi":"Arviointiasteikko","valueEn":"Assessment scale","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit","valueEn":"Assessment criteria","valueSv":""},"content":{"valueFi":"The course unit utilizes a numerical grading scale 1-5. In the numerical scale zero stands for a fail. Read more about assessment criteria at the University of Oulu webpage.","valueEn":"The course unit utilizes a numerical grading scale 1-5. In the numerical scale zero stands for a fail. Read more about assessment criteria at the University of Oulu webpage.","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 2","valueEn":"Evaluation criteria 2","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 3","valueEn":"Evaluation criteria 3","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Arviointikriteerit 4","valueEn":"Evaluation criteria 4","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Pääasiallinen opetuskieli","valueEn":"Primary Teaching Language","valueSv":""},"content":{"valueFi":"englanti","valueEn":"English","valueSv":"engelska"}},{"title":{"valueFi":"Taso","valueEn":"Level","valueSv":""},"content":{"valueFi":"Syventävät opinnot","valueEn":"Advanced Studies","valueSv":"Syventävät opinnot"}},{"title":{"valueFi":"Oppiaine","valueEn":"Subject","valueSv":""},"content":{"valueFi":"Prosessitekniikka","valueEn":"Process Engineering","valueSv":""}},{"title":{"valueFi":"Vastuuhenkilöt","valueEn":"Person in charge","valueSv":""},"content":{"valueFi":"Mika Ruusunen, Aki Sorsa","valueEn":"Mika Ruusunen, Aki Sorsa","valueSv":"Mika Ruusunen, Aki Sorsa"}},{"title":{"valueFi":"Luokittelu","valueEn":"Classification","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}},{"title":{"valueFi":"Linkit","valueEn":"Links","valueSv":""},"content":{"valueFi":"","valueEn":"","valueSv":""}}]}