Cooperative driving in a connected vehicle (CV) environment has received increasing attention over the years due to its ability to enhance driving safety and efficiency. Despite many efforts that have been made in this field, the role of human drivers and pedestrians is frequently omitted. It is important to consider them to develop cooperative driving algorithms that are intelligent and robust to incorporate any uncertainty brought by humans. In this dissertation, a framework of a multi-driver in-the-loop driving simulator and a pedestrian in-the-loop digital twin system is introduced. Three important topics in cooperative driving were investigated using the developed framework: the effects of human-machine interface (HMI) design for cooperative driving, vehicle-pedestrian interaction under occlusion scenarios, and multi-vehicle decision-making at weaving segments. In the first topic, three HMIs were designed for collaborative speed adaptation following the skills, rules, and knowledge (SRK) taxonomy. The HMI designs were tested using a multi-driver simulator, and the results showed that the graphic-based HMI improved cooperative driving performance and was preferred by the participants. In the second task, a Digital Twin framework for CV and pedestrian in-the-loop simulation was proposed based on Carla-Sumo Co-simulation and Cave automatic virtual environment (CAVE). The effects of Vehicle-Pedestrian (V2P) warning systems under occlusion scenarios were investigated for different connectivity and vehicle automation levels. In the third task, an edge-enhanced graph attention deep reinforcement learning algorithm was developed to aid autonomous vehicles in diverging at weaving segments. The results showed that the proposed algorithms outperformed existing models and performed well in real-world driving scenarios. The dissertation provides insights into developing safe and efficient cooperative driving algorithms and applying advanced simulation technologies to human-in-the-loop cooperative driving testing.

The overall goal of this work is to create an open-source digital twin of the wire arc directed energy deposition process using robot operating system 2 for interpass temperature regulation of a maraging steel alloy. This framework takes a novel approach to regulating the interpass temperatures by using in-situational infrared camera data and a closed loop feedback control that is enabled by robot operating system 2. This is the first implementation of robot operating system 2 for wire arc directed energy deposition and this framework outlines a sensor and machine agnostic approach for creating a digital twin of this additive manufacturing process. In-situ control of the welding process is conducted on a maraging steel alloy demonstrating interpass temperature regulation leads to improved as-built surface roughness and more consistent as-built hardness. An evaluation of three distinct weld modes: Pulsed MIG, CMT MIX, and CMT Universal and two primary process parameters: travel speed and wire feed speed was conducted to identify suitable process windows for welding the maraging alloy. Single track welds for each parameter and weld mode combination were produced and evaluated against current weld bead metrics in the literature. Non destructive profilometry and destructive characterization were performed on the single track welds to evaluate geometric features like wetting angle, dilution percentage, and cross sectional area. In addition, the role of material feed rate on heat input and the cross sectional area was examined in relation to the as-built hardness. The robot operating system 2 digital twin provides a visualization environment to monitor and record real time data from a variety of sensors including robot position, weld data, and thermal camera images. Point cloud data is visualized, in real time, to provide insight to the captured weld meta data. Capturing in-situ data from the wire arc directed energy deposition process is critical to establishing an improved understanding of the process for parameter optimization, tool path planning, with both required to build repeatable, quality components. This work presents an open-source method to capture multi-modal data into a shared environment for improved data capture, data sharing, data synchronization, and data visualization. This digital twin provides users enhanced process control capabilities and greater flexibility by utilizing the robot operating system 2 as a middleware to provide interoperability between sensors and machines.

This dissertation aims to provide critical methodological advancements for sensor fusion and physics-informed machine learning in metal additive manufacturing (MAM) to assist practitioners in detecting quality control structural anomalies. In MAM, there is an urgent need to improve knowledge of the internal layer fusion process and geometric variation occurring during the directed energy deposition processes. A core challenge lies in the cyclic heating process, which results in various structural abnormalities and deficiencies, reducing the reproducibility of manufactured components. Structural abnormalities include microstructural heterogeneities, porosity, deformation and distortion, and residual stresses. Data-driven monitoring in MAM is needed to capture process variability, but challenges arise due to the inability to capture the thermal history distribution process and structural changes below the surface due to limitations in in-situ data collection capabilities, physical domain knowledge integration, and multi-data and multi-physical data fusion. The research gaps in developing system-based generalizable artificial intelligence (AI) and machine learning (ML) to detect abnormalities are threefold. (1) Limited fusion of various types of sensor data without handcrafted selection of features. (2) There is a lack of physical domain knowledge integration for various systems, geometries, and materials. (3) It is essential to develop sensor and system integration platforms to enable a holistic view to make quality control predictions in the additive manufacturing process. In this dissertation, three studies utilize various data types and ML methodologies for predicting in-process anomalies. First, a complementary sensor fusion methodology joins thermal and ultrasonic image data capturing layer fusion and structural knowledge for layer-wise porosity segmentation. Secondly, a physics-informed data-driven methodology for joining thermal infrared image data with Goldak heat flux improves thermal history simulation and deformation detection. Lastly, a physics-informed machine learning methodology constrained by thermal physical functions utilizes in-process multi-modal monitoring data from a digital twin environment to predict distortion in the weld bead. This dissertation provides current practitioners with data-driven and physics-based interpolation methods, multi-modal sensor fusion, and anomaly detection insights trained and validated with three case studies.

The Advanced Manufacturing section at ÅF Pöyry AB is exploring the possibilities of virtual commissioning and digital twins. As part of this exploration, this thesis sets out to demonstrate a method of developing scalable, reusable and realistic digital mechatronic models – the heart of a digital twin – for the virtual environment in RobotStudio. Research has shown that one of the major obstacles to implementing virtual commissioning as a standard in industry today is the lack of scalable and reusable digital twins. This is also the experience of ÅF Pöyry AB. After reviewing existing and proposed methods for developing digital twins, this thesis explains the necessary steps for developing a SmartComponent in RobotStudio, using the programming language C#. The results show that the SmartComponent developed is scalable and thus reusable. It works with grippers with any number of fingers and allows gripping by applying pressure to the target object from both the outside and the inside. It is also realistic in the sense that the interaction between the grippers and the objects to be picked in the virtual environment behaves and looks like it does in reality. The implementation of the SmartComponent developed is much faster and less complex than the method used today at ÅF Pöyry AB. The downsides of the developed method are the added competence required of the automation engineer and the risk that the digital twin may not be future-proof. / Avdelningen Advanced Manufacturing på ÅF Pöyry AB utforskar möjligheter med ”Virtual Commissioning” och ”Digital Twins”. Som ett led i detta projekt har syftet med detta examensarbete varit att visa ett sätt att utveckla en skalbar, återanvändbar och realistisk digital mekatronisk modell för den virtuella miljön i RobotStudio. Tidigare forskning har visat, i linje med ÅF Pöyry AB:s satsning, att ett av de stora hinder för att Virtual Commissioning ska kunna implementeras som standard i industrin idag är bristen av skalbara och återanvändbara digitala tvillingar. Efter en genomgång av den befintliga och föreslagna metoden för att utveckla digitala tvillingar presenteras de nödvändiga stegen för att utveckla en SmartComponent för RobotStudio, med programmeringsspråket C#. Resultaten av utvecklingen och testen har visat att den utvecklade SmartComponent är skalbar och återanvändbar: den fungerar med gripare oavsett antal fingrar och den tillåter gripning både genom att applicera tryck på plockobjektet från utsidan och insidan. Den är också realistiskt på så vis att interaktionen mellan griparen och objekten som ska plockas i den virtuella miljön beter sig och ser ut som i verkligheten. Implementeringen av den utvecklade SmartComponent är också mycket effektivare och mindre komplex jämfört med den metod som används idag på ÅF Pöyry AB. Nackdelarna med den föreslagna metoden är de extra kompetenskraven för automationsingenjörer och risken att den digitala tvillingen inte är framtidssäker.

This thesis presents the design and prototype implementation of a digital twin based on a knowledge graph for Internet of Things (IoT) platforms. The digital twin is a virtual representation of a physical object or system that must continually integrate and update knowledge in rapidly changing environments. The proposed knowledge graph is designed to store and efficiently query a large number of IoT devices in a complex logical structure, use rule-based reasoning to infer new facts, and integrate unanticipated devices into the existing logical structure in order to adapt to changing environments. The digital twin is implemented using the open-source TypeDB knowledge graph and tested in a simplified automobile production line environment. The main focus of the work is on the integration of unanticipated devices, for which a similarity metric is implemented to identify similar existing devices and determine the appropriate integration into the knowledge graph. The proposed digital twin knowledge graph is a promising solution for managing and integrating knowledge in rapidly changing IoT environments, providing valuable insights and support for decision-making. / I den här avhandlingen presenteras utformningen och prototypimplementeringen av en digital tvilling baserad på en kunskapsgraf för IoT-plattformar (Internet of Things). Den digitala tvillingen är en virtuell representation av ett fysiskt objekt eller system som måste integrera och uppdatera kunskap i snabbt föränderliga miljöer. Den föreslagna kunskapsgrafen är utformad för att lagra och effektivt söka efter en stor uppsättning IoT-enheter i en komplex logisk struktur, använda regelbaserade resonemang för att härleda nya fakta och integrera oväntade enheter i den befintliga logiska strukturen för att anpassa sig till föränderliga miljöer. Den digitala tvillingen genomförs med hjälp av kunskapsgrafen TypeDB med öppen källkod och testas i en förenklad miljö för bilproduktion. Huvudfokus ligger på integrationen av oväntade enheter, för vilka ett likhetsmått implementeras för att identifiera liknande befintliga enheter och bestämma lämplig integration i kunskapsgrafen. Den föreslagna kunskapsgrafen för digitala tvillingar är en lovande lösning för att hantera och integrera kunskap i snabbt föränderliga IoT-miljöer, vilket ger värdefulla insikter och stöd för beslutsfattande. / Esta tesis presenta el diseño e implementación de un prototipo de gemelo digital basado en un grafo de conocimiento para plataformas de Internet de las Cosas (IoT). El gemelo digital es una representación virtual de un objeto o sistema físico que debe integrar y actualizar continuamente el conocimiento en entornos que cambian rápidamente. El grafo de conocimiento propuesto está diseñado para almacenar y consultar eficientemente un gran número de dispositivos IoT en una estructura lógica compleja, utilizar el razonamiento basado en reglas para inferir nuevos hechos e integrar dispositivos imprevistos en la estructura lógica existente para adaptarse a los cambios del entorno. El gemelo digital se implementa utilizando el grafo de conocimiento de código abierto TypeDB y se prueba en un entorno simplificado basado en una línea de producción de automóviles. El objetivo principal del trabajo es la integración de dispositivos no previstos, para lo cual se implementa una métrica de similitud para identificar dispositivos existentes similares y determinar la integración adecuada en el grafo de conocimiento. El grafo de conocimiento propuesto es una solución prometedora para la gestión del conocimiento y la integración en entornos IoT que cambian rápidamente, proporcionando información valiosa y apoyo a la toma de decisiones.

In order to succeed with the Sustainable Development Goals, the mining of minerals will need to not only continue, but increase in the coming years. The extraction of minerals such as gold and cobalt is often associated with human rights violations and the financing of criminal enterprises. This has led to increased pressure on firms to implement effective responsible sourcing practices. While often seen as a major challenge to many firms, if leveraged correctly, responsible sourcing can be turned into significant competitive advantages and increased supply chain visibility. Given the need for more research in this area, the aim of this study is to understand what responsible sourcing practices are used among manufacturing companies so that an approach for responsible sourcing of minerals can be developed. Using a qualitative research design and following a systematic combining approach, interviews with large industrial manufacturers were conducted. Using thematic analysis, this thesis identifies the main drivers, enablers, barriers, and strategies used by manufacturing companies. While the findings show that responsible sourcing is on the agenda for all companies, it is clear that some firms take responsible sourcing more seriously than others. Therefore, it is suggested that firms need to depart from a cost-centric perspective and instead see the benefits and long-term value generated from responsible sourcing. Furthermore, the findings suggest that some companies are becoming increasingly aware of the need to know their supply chain, and how responsible sourcing practices can be beneficial by providing supply chain visibility. However, the current practices are limited because they are an inherently static representation of a dynamic system. The implementation of a supply chain digital twin is therefore presented as a potential way for firms to improve their responsible sourcing practices while at the same time gaining substantial business value. / För att lyckas med målen för hållbar utveckling måste brytningen av mineraler inte bara fortsätta, utan även öka under de kommande åren. Utvinning av mineraler som guld och kobolt är ofta förknippad med kränkningar av mänskliga rättigheter och finansiering av kriminella organisationer. Detta har lett till ett ökat tryck på företag att införa effektiva metoder för ansvarsfullt inköp. Även om det ofta ses som en stor utmaning för många företag kan ansvarsfullt inköp, om det används på rätt sätt, omvandlas till betydande konkurrensfördelar och bidra till ökad synlighet i leveranskedjan. Med tanke på behovet av mer forskning på detta område är syftet med den här studien att förstå vilka metoder för ansvarsfullt inköp som används bland tillverkningsföretag, så att ett tillvägagångssätt för ansvarsfullt inköp av mineraler kan utvecklas. Genom en kvalitativ forskningsdesign och enligt en systematisk kombinationsmetod genomfördes intervjuer med stora tillverkande företag. Med hjälp av tematisk analys identifieras i denna avhandling de viktigaste drivkrafterna, möjliggörarna, hindren och strategierna som används av tillverkningsföretag. Resultaten visar att ansvarsfullt inköp står på agendan för alla företag, men det är tydligt att vissa företag tar ansvarsfullt inköp på större allvar än andra. Därför föreslås det att företag måste avvika från ett kostnadsfokuserat perspektiv och istället se fördelarna och det långsiktiga värdet som genereras av ansvarsfullt inköp. Dessutom tyder resultaten på att vissa företag blir allt mer medvetna om behovet av att känna till sin leverantörskedja och hur ansvarsfulla inköpsmetoder kan vara fördelaktiga genom att ge större synlighet i leverantörskedjan. De nuvarande metoderna är dock begränsade eftersom de är en statisk representation av ett dynamiskt system. Implementeringen av en digital tvilling i försörjningskedjan presenteras därför som ett potentiellt sätt för företag att förbättra sina metoder för ansvarsfulla inköp samtidigt som de får ett betydande affärsvärde.

The intention to reduce greenhouse gas emissions in the aviation industry is generating high pressure to innovate, which is also leading to an increasing need for improvements in the development process, especially as this is already subject to major changes due to changing products and value creation systems. In the future, the development process should be more digitalized and information better integrated in order to optimize the supply of information to developers. To this end, the following article presents a digital twin for product development, which is being developed as part of a research project on cross-lifecycle integration through digital twins in collaboration with Rolls-Royce Electrical and other research partners. The focus is on describing the conception of the digital twin, which produces a concept that is as user centric as possible based on user stories in order to specifically serve existing needs. The concept of the digital twin will be developed based on the current as-is process and the existing system landscape as well as the use cases derived from the user stories and presented here.

Detta projekt är givet som ett kandidatarbete i mjukvaruutveckling vid Linköpingsuniversitet, i kursen TDDD96 Kandidatprojekt i programvaruutveckling. Arbetet är utfört aven grupp tredjeårsstudenter på D- och U-programmen.Projektet ges av forskargruppen för integrerad systembiologi på IMT LiU, som utvecklarmatematiska modeller av biologiska system. Dessa modeller kan användas för att förståsystemen bättre, eller som beslutsstöd inom farmakologi och vård. Forskargruppens fokusför tillfället är att sammankoppla modeller för olika delar av människokroppen till en helhetsbildsom beskriver delsystemens samverkan.Denna helhetsbild för en särskild individs hälsotillstånd kallas för en digital tvilling, förvilken detta projekt ämnar framställa ett användargränssnitt.Användargränssnittet skall erbjuda grafer över hälsoparametrars förändring över tid,och användaren ska kunna ta fram olika sådana genom att interagera med gränssnittet.Utöver framtagning av själva gränssnittet, skall en brygga mellan applikationen ochkundens modeller tas fram. Detta har gjorts genom en version av programmet OpenCOR,vilket forskarna använder sig av, som exponerar ett API i Python. Detta API sammankopplatmed en server kallas i projektet för motor.

Genom att använda sig utav en virtuell kopia utav en produktionscell kan programmering och funktionstester av olika paneler testas i ett tidigt stadie. En virtuell kopia bidrar också till enklare felsökning och minskning av kostnader vid idrifttagning. Tanken med projektet är att undersöka i vilken utsträckning som emuleringsmodellen kan ersätta den riktiga cellen vid ett funktionstest för leverantören. Det som också undersöks är i vilken utsträckning riktiga CAD-ritningar kan användas och vilka krav som ställs på ritningarna för att underlätta emulering. Projektet hade flera utmaningar och en av dem som uppkom under projektets gång var problemet med att det inte gick att emulera säkerhetssystemen. Detta löstes genom att bygla alla säkerhetskretsar i PLC-programmet. En viktig del i emulering är kommunikation mellan de olika programvarorna i systemet. I projektets visade det sig fördelaktigt att dela upp programmen i emuleringssystemet för att fördela resurserna över tre datorer. Att använda sig utav en emuleringsmodell istället för en riktig produktionscell är fortfarande i forskningsstadiet men genom projektet har många användningsområden identifierats och skulle kunna förändra idrifttagning i framtiden. / Using a virtual twin of a production cell, makes it possible for programming and different functional testing of panels to be performed in early stages of development. A virtual twin contributes to a simpler debugging and to identify problems and minimize cost in commissioning of the production cell. The aim for the project is to investigate how well an emulated cell will perform compared to the real production cell in a factory acceptance test. Another objective is to investigate how you can use real CAD models in the emulation and what type of criteria the models should meet. The project had a lot of challenges and one of them was the difficulty to emulate the safety systems. This was solved by bypassing the safety in the PLC program. One important thing about emulation is communication between the different software used in the system. In this project, it proved successful to distribute the software on three computers to ease the workload of the programs used in the emulation. To use the emulated model instead of the real system is still in the research phase but in this project a lot of useful applications could be identified that could change commissioning in the future.

This thesis describes the implementation of a Digital Twin tied to Virtual Reality environment thatcould, by easy means be expanded to Augmented Reality-solution. The field is of interest due to thefact that movement into Industry 4.0 puts the traditional operator in a new seat of work. Previoushands-on tasks are replaced with system monitoring and supervision roles. New interconnectedindustrial hardware allows for extensive data collection, while interactive technology like VR/ARhelps monitoring live systems in completely new manners. An operator can overview and debugindustrial systems while not even being in close proximity of the physical system. This provides theopportunity to increase the level of system information presented to the operator. The Cyber PhysicalFactory created by Festo was targeted to be represented as a digital twin. The question asked: What arethe advantages and/or disadvantages of monitoring and troubleshooting a Festo CP-Factory by meansof a digital twin-driven visualization? proved to be extensive and the work included mapping ofimportant factory data and DRM-research to find visual improvements between the provided solutionsby Festo, and an implemented digital twin. The solution we produced focuses on overview anddebugging and it connects to OPC-servers on each mapped module of the Cyber Physical Factory andacquires the data. This data can then be used to expand, test and debug previous sessions. Each realimplementation of a factory has some type of logging of data, our solution allows visualization of thoselog entries as close to reality as possible, reducing the need to search databases for indications ofproblems. The Unity 3D created software also handles dynamic connections where the operator canmodify which nodes to connect to in an intuitive way, this enables our software to abstract and modifyinformation outside of the source code.