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Emergence of the new technological trends such as Open Platform Communications Unified Architecture (OPC UA), Industrial Ethernet, cloud computing and the 5th wireless network (5G) enabled the implementation of Cyber-physical System (CPS) with flexible, configurable, scalable and interoperable business models. This provides new opportunities for the process automation systems. On the other hand, the constant urge of industries for cost and material efficient processes demands a new automation paradigm with the latest tools and technologies which should be taken into account while teaching future automation engineers. In this thesis, the modern teaching environment for process automation is designed, implemented and described. This work explains the connections, configurations and the test of three mini plants including the Multiple Heat Exchanger, the Three-tank system and the Mixing Tank. In addition, OPC UA communication between the server and its clients has been tested. The plants are a part of the state of the art of the architecture that provides the access of ABB 800xA to the cloud services via OPC UA over the 5G test wireless network. This new paradigm changes the old automation hierarchy and enables the cross layered communication in the old architecture. This modern teaching environment prepares the students for the future automation challenges with the latest tools and merges data analytics, cloud computing and wireless network studies with process automation. It also provides the unique chance of testing the future trends together in this unique process automation setup.

The main aim of this thesis is to develop a new temperature profile control strategy for kaolin calcination in the multiple hearth furnace (MHF) in order to improve the quality of the product. The overall control strategy for the MHF is developed as a three level control hierarchy: optimizing level, stabilizing level, and basic level. In the literature part of the thesis, first, the kaolin and its formation process is discussed. Next, the general information about calcination process is provided and the calcination of kaolin is discussed. Finally, few past researches having similar objective to this study are reviewed to study the various different control approaches developed so far and the possibility to implement them in our study. In the experimental part, analysis of the process is carried using the experimental data. During the data analysis, activation/ deactivation of the exothermic reaction in the hearth 4 is seen, which is crucial in determining the temperature profile of the furnace. Hence, the soft sensor based on the energy balance to estimate the intensity of the exothermic reaction, which plays a key role in developing the control strategy for the MHF, is developed. Both the static and dynamic energy balance equations are presented, calculated and compared in order to study the dynamic behaviour in the process. It is seen that the dynamic energy balance provides more accurate results than the static energy balance due to the consideration of the transition period.

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 t

Modern industrial processes typically have complex interconnections among process equipment and units. A fault can easily propagate far beyond its origin, making it difficult to locate the root cause and to identify its propagation paths. Thus, the latest approach for identifying fault propagation paths uses qualitative models, e.g., topology-based models, for improving the results acquired from the data-driven methods of causal analysis. However, the current approach includes no display of the fault propagation paths in process monitoring systems, which could enable the visualisation of the spread of fault effects. In this thesis, the aim is to develop and to test a new technique which enables a process monitoring system to display fault propagation paths, based on the causality matrix obtained from a process. A causality matrix is created using the Granger causality method, which contains the details of the fault propagation path. Subsequently, the causality matrix is refined using a connectivity matrix, which was obtained from a piping and instrumentation diagram (P&ID). Furthermore, the process monitoring system and the refined causality matrix are linked together, to transfer the fault propagation paths details to the process monitoring interface. A number of algorithms in the automation system are developed and implemented to accomplish the link. A flotation pilot process is the case study in this thesis, used for testing this technique. The experiment data acquired from the flotation pilot was analysed to generate a causality matrix, which is subsequently refined and stored in the database of the automation system. Hence, the fault propagation paths is visualised in the process monitoring system. Finally, this procedure confirmed that the propagation of the effects of a fault is better understood if the propagation path is visualised in the process monitoring system.

The rise in the demand of an alternative source of energy that can substitute the depleting fossil fuel has introduced new challenges in process industries. Today, biomass fuel is increasingly used as a renewable source of energy used for power production. The BioGrate boiler is one of the latest technologies that utilize biomass fuel for power production. These boilers need to cater to the power demand of the market without any interruptions in their operations. However, the heat content of biomass samples differs depending on their place of origin, their composition and their moisture content, thus introducing fluctuations in power production. Hence, uninterrupted operation of the boiler requires an efficient process monitoring method which can detect disturbances as early as and take corrective measures. The aim of this Master’s thesis is to develop a system for the mass and energy balance calculation for process monitoring of BioGrate boiler. These calculations are developed around each process unit of the BioGrate boiler using the measurements available at the Vilppula plant. However, since measurements inevitably contain random errors, a data reconciliation algorithm is developed to minimize the errors. The reconciliation algorithm ensures that the measurements satisfy the balance equations. The literature part of this thesis discusses the literature on the modelling of boilers based on the mass and energy balance calculations and introduces the concept of data reconciliation. It also describes the commercial software that is currently used for process monitoring in power plants. Based on the literature part, the balance calculation and the data reconciliation algorithms are developed in the experimental part. Balance calculations at steady-state and nonlinear data reconciliation methods are used in this thesis. In addition, a graphical user interface is developed to provide a user-friendly tool for executing the algorithms. The results obtained from the algor

Process disturbances always spread along the connected equipment in a plant and are detected in many places. In order to identify the root disturbance, many data-based fault detection and diagnosis (FDD) methods have been developed in recent years. However, most of these methods can generate spurious solutions. Several authors have observed that FDD methods are enhanced if topology information about the causal relationships of a process is considered as well. Generally, this topology information is manually created by using the process knowledge. However, such a way is always time-consuming and the result is imprecise. Hence, there is a requirement for an automated generation of effective topology-based causal models. This thesis developed a thorough approach to implement two types of causal models, i.e., a connectivity matrix and a causal digraph, based on piping and instrumentation diagrams (P&IDs). As the core development tools, AutoCAD P&ID and object-oriented programming (OOP) of MATLAB were used. The development included three procedures: generate topology data, define the class for generating causal models, and obtain the causal models by instantiating the class with the topology data. In conclusion, it appears that both the connectivity matrix and causal digraph manifest the internal relationship between different process components caused by material flows and signal flows in a clear way. Therefore, these models can play an important role in the research associated with the FDD methods.