Browsing by Author "Kortela, Jukka"

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  • Advanced teaching and process monitoring environment for the factory of the future
    (2017-03-23) Kortela, Jukka; Nasiri, Babak; Lahnalammi, Antton; Jämsä-Jounela, Sirkka-Liisa
     A4 Artikkeli konferenssijulkaisussa
    ABB Industrial IT Extended Automation System 800xA has been set up for centralized data collection, analysis, real-time monitoring, and advanced control. The ABB system is further expanded by cloud based advanced control and monitoring system. The state-of-the-art ABB setup includes OPC UA, providing a single entry point into a system. Each piece of equipment is automated using a dedicated PLC-station and different fieldbuses, diversifying the teaching and research benefits. The cloud based system will include an OPC UA client which allows access to ABB OPC Server using OPC UA Specifications. OPC UA scales very well in several directions. It allows OPC UA applications to run on embedded devices with very limited hardware resources, as well as on very powerful machines like mainframes. The final set up will run on the high velocity web framework Play that has been especially designed for Java and Scala. Play 2 provides native Akka support (toolkit and runtime) for Play applications enabling writing highly-distributed systems in the cloud. In addition, it follows model–view– controller (MVC) software design pattern, separating the software application into three interconnected parts: models, views, and controllers. The model manages the data, logic, and rules of the application. The monitoring and optimization algorithms are implemented in the model component. In addition, OPC UA client library will be utilized for reading and writing the data from the industrial processes. The proposed advanced teaching and process monitoring system is evaluated with test-algorithms implemented in the Spark cloud and the results are presented, analyzed, and discussed.
  • The advantages and disadvantages of biosimilar pharmaceuticals
    (2016-12-05) Kakko, Natalia
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • CIP - Pesunesteen lämpötilan stabilointi
    (2020-01-15) Pesonen, Kalle
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • Data reconciliation approach for accurate energy balance estimation in the multiple hearth furnace
    (2017-06-13) Tajuddin, Ibrahim
     Kemian tekniikan korkeakoulu | Master's thesis
  • Data-reconciliation based fault-tolerant model predictive control for a biomass boiler
    (2017) Sarkar, Palash; Kortela, Jukka; Boriouchkine, Alexandre; Zattoni, Elena; Jämsä-Jounela, Sirkka Liisa
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper presents a novel, effective method to handle critical sensor faults affecting a control system devised to operate a biomass boiler. In particular, the proposed method consists of integrating a data reconciliation algorithm in a model predictive control loop, so as to annihilate the effects of faults occurring in the sensor of the flue gas oxygen concentration, by feeding the controller with the reconciled measurements. Indeed, the oxygen content in flue gas is a key variable in control of biomass boilers due its close connections with both combustion efficiency and polluting emissions. The main benefit of including the data reconciliation algorithm in the loop, as a fault tolerant component, with respect to applying standard fault tolerant methods, is that controller reconfiguration is not required anymore, since the original controller operates on the restored, reliable data. The integrated data reconciliation-model predictive control (MPC) strategy has been validated by running simulations on a specific type of biomass boiler - the KPA Unicon BioGrate boiler.
  • Educational Setup for Service Oriented Process Automation with 5G Testbed
    (2017-12-01) Kortela, Jukka; Nasiri, Babak; Smirnov, Alexander; Lahnalammi, Antton; Jämsä-Jounela, Sirkka Liisa
     A4 Artikkeli konferenssijulkaisussa
    There is a constant challenge in process industry to reduce costs because of tight competition on the global market. On the other hand the advancement in the new technologies such as Open Platform Communications Unified Architecture (OPC UA), Industrial Ethernet, 5G, and cloud computing provide the possibility to implement cost effective Cyber-physical systems (CPS). This allows flexible, reconfigurable, scalable, interoperable business models. These trends in the process industry should be taken into account while teaching future engineers. In this article the modern process automation setup which includes three miniplants with optional 5G connectivity is described along with teaching approach for executing the students projects. Using this infrastructure students obtain knowledge with emerging industrial technology and become the actors of upcoming industrial revolution.
  • Entsyymien inhibitio lignoselluloosan hydrolyysissä
    (2016-10-24) Iivonen, Piia
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • Fault tolerant model predictive control (FTMPC) of the BioGrate boiler
    (2015) Kortela, Jukka
     School of Chemical Technology | Doctoral dissertation (article-based)
    Climate change and environmental concerns are forcing process industries to increase the share of sustainable resources in energy production. The utilization of biomass receives an increasing attention as a replacement for fossil fuels due to its wide availability and sustainability. However, the unpredictable variability of biomass properties, including moisture content, composition and heating value, results in disturbances, faults, and failures during the power plant operation, which creates additional barriers for a wider utilization of biomass.  This thesis focusses on the development of a fault tolerant model predictive control (FTMPC) scheme that addresses the challenges associated with the biomass utilization for power production in BioGrate boilers. The novelty of this scheme lies in the integration of soft-sensors measuring the unpredictable biomass properties with a fault accommodation mechanism.  The effectiveness of the developed FTMPC scheme is successfully tested with a dynamic simulator of the BioGrate boiler. This simulator is constructed using the industrial test data from the BioPower 5 CHP plant. In addition, industrial tests, conducted to evaluate the performance of the developed soft-sensors, confirm the prediction accuracy of the fuel moisture content and combustion power in the furnace. Subsequently, the economic evaluation of the soft-sensors integrated FTMPC scheme is presented.
  • Fault Tolerant Model Predictive Control for the BioPower 5 CHP Plant
    (2014) Kortela, Jukka; Jämsä-Jounela, Sirkka-Liisa
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The main aim of control of the BioGrate boiler is stable energy production, where a fuel bed height sensor is a critical element in the control of the BioGrate boiler and its faulty operation should thus be avoided. A fault tolerant model predictive control (FTMPC) has been developed to accommodate the fault in this fuel bed height sensor by active controller reconfiguration. The proposed FTMPC is tested with the BioPower 5 CHP plant data by simulation and finally the results are presented, analysed, and discussed.
  • Fault-tolerant model predictive control (FTMPC) for the BioGrate boiler
    (2015) Kortela, Jukka; Jämsä-Jounela, Sirkka-Liisa
     A4 Artikkeli konferenssijulkaisussa
  • Fuel moisture soft-sensor and its validation for the industrial BioPower 5 CHP plant
    (2013) Kortela, Jukka; Jämsä-Jounela, Sirkka-Liisa
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper presents a soft-sensor for on-line monitoring of fuel moisture in a furnace. The method utilizes combustion power estimation and a dynamic model of the secondary superheater. In addition, the time delays in detecting changes in moisture content of the fuel are small enough for the method to be used for controlling air and fuel feed and preventing steam and pressure oscillations. To verify the fuel moisture soft-sensor, experiments were performed at a BioPower 5 CHP plant, which utilizes BioGrate combustion technology for very wet biomass fuels with a moisture content as high as 65%. Finally, the results are analyzed and discussed.
  • Fuel-quality soft sensor using the dynamic superheater model for control strategy improvement of the Biopower 5 CHP plant
    (2012) Kortela, Jukka; Jämsä-Jounela, Sirkka-Liisa
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    This paper presents an enhanced method for estimating fuel quality in a BioGrate combustion process and the method’s use in control strategy improvement. This method is based on a dynamic model that makes use of combustion power estimates – which can be calculated based on the furnaces oxygen consumption – and that makes use of a nonlinear dynamic model of the secondary superheater. The paper focuses to estimate the most essential combustion parameters: fuel moisture and fuel flow. The time delay for detecting a change in fuel moisture and fuel flow is small enough for the method to be used for controlling both air and fuel feed, preventing any steam and pressure oscillations. The proposed control strategy is compared with the method currently used in the BioPower 5 CHP plant. Finally, the results are analyzed and discussed.
  • Improvement of load-following capacity of grate boilers based on the combustion power soft-sensor
    (2017) Kortela, Jukka; Jämsä-Jounela, Sirkka Liisa
     A4 Artikkeli konferenssijulkaisussa
    For improving the load-following capacity of existing grate boiler units, a model predictive control concept based on the combustion power soft-sensor is developed. Because the combustion power estimation has a very quick response to the primary air flow input, the load-following speed of the boiler control system will be improved considerably. The proposed model predictive control strategy is tested with the BioPower 5 combined heat and power plant data and the results are presented, analyzed, and discussed.
  • Industrial internet and its role in process automation
    (2016-04-12) Solovyev, Anatoly
     Kemian tekniikan korkeakoulu | Master's thesis
    Modern process automation undergoes a major shift in the way it addresses conventional challenges. Moreover, it is adapting to the newly arising challenges due to changing business scenarios. Nowadays, the areas of the automation that recently were rather separate start to merge and the border between them is fading. This situation only adds struggle to the already highly competitive production industry. In order to be successful, companies should adopt new approaches to the way their processes are automated, controlled, and managed. One of these approaches is the so-called Industrial Internet. It is the next step after the traditional paradigm of the process automation pyramid that leads to the new vision of interconnected processes, services, machines and people. However, general company does not usually eager to implement the new technology to its business. One of the reasons for this is that it does not see the advantages that the Industrial Internet brings. This is due to the lack of sufficient number of successful implementation examples in various industrial areas and of clear business scenarios for the use of the Industrial Internet. Aim of the presented thesis is to create a convincing Industrial Internet application scenario. For the implementation, a mineral concentration plant was chosen as one of the industrial premises that possesses the shortage of the Industrial Internet examples. Literature review section describes the process automation state of art. It lists and reviews the research and development initiatives related to the Industrial Internet. Moreover, the Industrial Internet fundamentals are given. Finally, it describes the Industrial Internet applications and the case studies. In the practical part, at first, the description of the mineral concentration plant is given. Then, the next section describes the Industrial Internet application scenario. In the following section technical guidelines for the system implementation are given. Also, in the concluding part of the thesis the future direction of research work are discussed.
  • Integroidut prosessien ohjaus- ja tuotannonhallintajärjestelmät
    (2012-11-30) Pöri, Lauri
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • IoT-laitteet prosessiteollisuudessa
    (2015-04-29) Oleander, Toni
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • Joustavat energiaverkot ja järjestelmät
    (2016-05-08) Sippo, Siiri
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • Kierteisen kelan lämmönsiirtimen mallinnus
    (2023-05-08) Louhi, Luka
     Kemiantekniikan korkeakoulu | Bachelor's thesis
  • Kierteisen kelan lämmönsiirtimen mallinnus ja parametrien optimointi
    (2024-05-05) Jeskanen, Julius
     Kemiantekniikan korkeakoulu | Bachelor's thesis
    Kandidaatintyössä tutkittiin lämmönsiirtoa mallintamisen näkökulmasta. Tämä työ sisältää kokeellisen osuuden, jossa mallinnettiin pilottilämmönsiirrin Python ohjelmointikielellä. Lämmönsiirrin koostuu kierteisestä putkipuolesta ja sylinterimäisestä vaippapuolesta. Lämmönsiirtolaitteistoon on kytketty ABB system 800xA-ohjausjärjestelmä, joka mahdollistaa syötteiden säädön ja datan keräämisen. Työ on jaettu viiteen osaan, jotka ovat johdanto, kirjallisuuskatsaus lämmönsiirtoon ja mallintamiseen, lämmönsiirtimen mallinnus, parametrien optimointi ja tulosten validointi. Tässä työssä lämmönsiirrin mallinnettiin fysikaaliskemikaalisen mallin avulla, joka vähentää laskennallisia vaatimuksia huomattavasti. Toteutettu malli perustui lämmönsiirtimen jakamiseen useaksi tasealueeksi, joille kullekin voidaan laskea energiatase. Tämä tase muodostuu virtauksen mukana tulevan nesteen lämpömäärään, sekä lämmönsiirtimen putki- ja vaippapuolen väliseen konvektiiviseen lämmönsiirtoon. Konvektiivisessa lämmönsiirrossa merkittävä termi on lämmönsiirtokerroin 𝑈, joka voidaan esittää lämmönsiirtimeen sidottujen parametrien 𝐶 ja 𝑛 avulla. Työn teoriaosassa käsitellään kirjallisuudessa käytettyjä malleja, joiden lämmönsiirtokertoimen estimointi perustuu samoihin menetelmiin kuin tässä työssä. Kokeellisessa osassa validoitiin mallin syötteinä käytetyt nesteiden tilavuusvirtaa mittaavat virtausmittarit, jotta mallin virhe ei johtuisi syötteiden virheistä. Mallin syötteinä käytettiin syötettyjen nesteiden tilavuusvirtoja ja lämpötiloja. Lämmönsiirtokertoimen 𝑈 parametrit optimoitiin jakamalla lämmönsiirtimestä kerätty, 1079:stä datapisteestä koostuva syötedata jaettiin neljään osaan, joista kahta käytettiin parametrien koulutusdatana ja kahta mallin validointidatana. Koulutusdatan perusteella voitiin lämmönsiirtokertoimelle optimoida parametrit 𝐶 ja 𝑛, joiden arvoiksi saatiin 0,01 ja 0,60. Mallin tavoitefunktiona käytettiin absoluuttista keskivirhettä. Käyttämällä optimoituja parametreja malliin syötettiin validointidatasarjat, joita verrattiin mallin tuottamiin tuloksiin. Validointidatasarja 1 tuotti keskivirheen 1,23 ◦C ja validointidatasarja 2 tuotti keskivirheen 0,403 ◦C. Mallin tyydyttävään suorituskykyyn vaikutti eniten parametriavaruuden laajuus ja sen karkea resoluutio. Mallin suorituskykyyn vaikuttaneita tekijöitä on arvioitu laajemmin luvussa 4.2. Mallin hyödyntämistä vähemmän tarkkuutta vaativissa sovelluksissa voidaan saatujen tulosten nojalla pitää varteenotettavana vaihtoehtona.
  • Kuparin oksidien lämmönjohtavuus
    (2016-09-26) Stubb, Janne
     Kemiantekniikan korkeakoulu | Bachelor's thesis