In this thesis, a proof of concept of a digital twin of a type of reheating furnace, the walking beam furnace, is presented. It is created by using a machine learning concept called a neural network. The digital twin is trained using real data from a walking beam furnace located in Swerim AB, Luleå, and is taught to predict the temperature in the furnace using air, fuel and pressure as inputs. The machine learning technique used is an artifical neural network in the form of a multilayer perceptron model. The resulting model consists of 3 layers, input, hidden and output layer. The hyperparameters is decided by using grid search cross validation. The hyperparameters chosen to use in this thesis was amount of epochs, optimizer, learning rate, batch size, activation function, regularizer and amount of neurons in the hidden layer. The final settings for these can be found in table. The digital twin is then evaluated comparing predicted temperatures and actual temperatures from the measured data. The end result shows that the twin performs reasonably well. The predictions differs from measured temperature with a percentage around 0.5% to 1.5%.

This master thesis will cover a way to automatically generate a formal model for plant verification from plant traces. The solution will be developed from trace data, stemming from a model of a digital twin of a physical plant. The final goal is to automatically generate a formal model of the plant that can be used for model checking for verifying the safety and functional properties of the actual plant. The solution for this specific setup will be generalized and a general approach for other systems will be discussed. Furthermore, state machine generation will be introduced. This includes generating state machine data from traces, and in the future is planned be used as an intermediate step between the trace data and model generation. The digital twin solution used in this project is a joint setup in Visual Components and nxtSTUDIO. The symbolic model checker NuSMV is utilized in order to verify the functional properties of the plant. / I detta examensarbete utforskas ett sätt att generera formella modeller av en process via inspelningar av dennes beteende. Lösningen är utvecklad från data över processens beteende, som tas upp av en digital tvilling. Det slutgiltliga målet är att med hjälp av den digitala tvillingen automatiskt generera en modell som kan användas för att verifiera säkerhet och funktioner för den riktiga processen. Lösningen blir sedan generaliserad för att i framtiden kunna bli applicerad på andra processer. Ett sätt att generera tillståndsmaskiner kommer läggas fram. Detta sätt kommer generera data för tillståndsmaskinerna genom den digitala tvillingens beteende och i framtiden planeras att användas som ett mellansteg för att generera de slutliga modellerna.  Den digitala tvillingen som används i det här projektet är implementerat av Aalto universitet, och i flera program. Den visuella delen, som även spelar in tvillingens beteende, är implementerad i Visual Components. En kontroll för den digitala tvillingen är gjord i nxtSTUDIO. Verktyget för att verifiera modellens säkerhet och funktioner är gjord i NuSMV.

With the advance of the fourth industrial revolution, the manufacturing industry is increasingly changing. The intelligent networking of machines and the collection of real-time data opens up new possibilities for data-based decision making. One of those applications is the digital twin. Those are digital copies of physical objects that represent the behavior of their real-world counterparts. Therefore they consist of several models to describe this behavior. The use of digital twins for virtual commissioning has been proven to reduce real commissioning time as errors can be identified and fixed before they occur. Especially in the manufacturing industry virtual commissioning is used for expensive assets such as whole manufacturing lines. This thesis investigates how a three-dimensional model of a manufacturing cell can be connected to its real-world counterpart. The aim is to develop a reference model. A virtual commissioning model of a real manufacturing cell is created to evaluate the main components of the reference model. The outcome of this study is a theoretical reference model to connect a collaborative manufacturing cell with a digital twin. Through the connection, the three-dimensional simulation model acts as a video of the real cell. The reference model can serve as the base for further research such as remote troubleshooting or to improve existing models.

In our current environment, where we increasingly become dependent on the internet, the definition of living smart is widely used. Smart living involves original and innovative solutions to make life more efficient, controllable, economical, productive, integrated and sustainable. The Internet of Things (IoT) helps people with the lifestyle of smart living and helps them gain complete control. IoT does not only offer smart devices for the home, such as Google Home or Alexa. It is also essential for small and big businesses. The ability to transfer data over a network without any human interaction is needed in today's society. Organisations in multiple industries are using IoT to improve decision-making and overall quality of life for their employees. One way of using the IoT infrastructures is a concept called digital twin or a Digital Twin of an Organization (DTO). Since an organisation is constantly evolving, keeping the DTO aligned with the organisation will require an infrastructure that lends itself to be highly flexible and maintainable. The EA Blueprint Pattern was proposed to help achieve a flexible and maintainableDTO. However, there are limited practical instantiations of this pattern that can evaluate its utility. This project will therefore perform a practical evaluation and analysis of the pattern.

There is growing interest in the concept of digital twins (DTs) among software engineers and researchers. As an emerging topic, DTs are a promising paradigm to enhance the predictability, safety, and reliability of cyber-physical systems in different domains. Despite the increasing trend, it is continually challenging to decide the best approach to implement DTs. Moreover, to the best of the author's knowledge, it was found that there is a lack of conducted research and no systematic reviews on DTs in the transportation industry, especially in the area of railway systems. Therefore, following the systematic literature review method, this thesis work has identified 363 articles in four digital libraries, of which 60 primary articles were included to address three research questions. The review shows that most of the reviewed articles focus on the railway subarea maintenance and inspection, the DT enabling technology artificial intelligence is the most coupled technology. An in-depth analysis found that most of the articles apply machine learning algorithms and techniques in DTs to detect faults, predict failures, make automated decisions, and monitor health status to optimize railway systems. It was also found that interoperability is the most discussed challenge, where the difficulty is to transmit operational data in real-time and also achieve real-time decision making. Furthermore, the analysis shows several opportunities and advantages of DTs, such as reducing maintenance costs and the positive contribution to a reduction in freight transport by road. Finally, based on the findings of the conducted review, a guideline to support the design of a DT for predictive maintenance in railways in the form of a flowchart is presented and explained.

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Örebro University and Akademiska Hus have started an initiative towards smart buildings. Avery important role to this is Digital Twin for buildings. Digital twin for buildings is a virtualcopy of a physical building. And by adding a Data Driven Simulation System, an even moresmart building could be achieved. Given a humidity-, temperature-, illuminance- and motionsensor in a specific corridor at the Örebro University, this thesis will ascertain what can bedone by creating a Data Driven Simulation System and using these sensors to achieve thedesired smart building. In this thesis, a simulation was created with simulated sensors andpedestrians. The simulation is a clone of the real world, by using real life sensors andapplying the data to the simulated sensors, this was partially achieved.

The use of virtual commissioning has increased in the last years, but there are still challenges before the software code validation method is widespread in use. One of the additions to virtual commissioning is basing it on a digital twin to allow for improved accuracy. The aim of this thesis is to review existing standards and approaches to developing virtual commissioning, as well as to explore the definitions. The chosen approach to achieve the aim, is to perform a literature review of existing research papers and interviews with knowledgeable people in the industry. First, the definitions and classifications are reviewed, then the approaches for development of virtual commissioning and digital twins are explored in the literature. In three interviews with people of varying backgrounds and competences, the views of the virtual technologies are assessed to provide insight in the industry. The findings of the literature review and interviews are among others, the apparent need for standardisation in the field and that a sought-after standard in the form of ISO 23247-1 is under way. Furthermore, the digital twin is a concept with a promising future in combination with other technologies of Industry 4.0. In conclusion, this thesis provides a deep review of the challenges and possibilities of virtual commissioning and the digital twin and could be used as starting point for further research in standardisations and improvements sprung from the new standard.

In this thesis, the trade-offs between latency and transmitted data volume in vehicle-to-cloud communication for different choices of application layer messaging protocols and binary serialization formats are studied. This is done with the purpose of getting enough performance improvement to enable delay-sensitive Intelligent Transport System (ITS) features, and to reduce data usage in mobile networks. The studied protocols are Constrained Application Protocol (CoAP), Advanced Message Queuing Protocol (AMQP) and Message Queuing Telemetry Transport (MQTT), and the serialization formats studied are Protobuf and Flatbuffers.  The results show that CoAP — the only User Datagram Protocol (UDP) based protocol — has the lowest latency and overhead while not being able to guarantee reliable transfer. The best performer that can guarantee reliable transfer is MQTT. For the serialization formats, Protobuf is shown to have three times smaller serialized message size than Flatbuffers and also faster serialization speed. Flatbuffers is the winner in the case of memory use and deserialization time, which could make up for the poor performance in other aspects of data processing in the cloud. Further, the implications of these results in ITS communication are discussed suggestions made into future research topics.

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