This thesis work investigates the possibilities and limitations of using digital twin technology to create virtual automation lines which can be used in education and research to conduct automation labs virtually. The PTC automation line at University West has been used as a case study in this thesis. The digital twin created in this work consists of three key parts: a virtual model of the automation line created in Visual Components Premium 4.2, system control (PLC-control program) created in TwinCat 3, and a Beckhoff ADS communication protocol that connects the virtual model with the PLC program. Using a virtual model of industrial-like lab equipment in place of a real system can bring several benefits. It can increase visibility and safety in the system. It can also increase the accessibility of the system. Conducting virtual labs and experiments can also help in reducing the total cost of the system. The virtual twin of the automation line built in this work can be used to help the users to conduct automation labs and experiments virtually and to test their PLC programs offline.

At Epiroc’s drill rigs a safe system is installed to make sure the vehicle is driven in a safe manner. In the development both machine tests and hardware-in-the-loop (HIL) tests have been performed but when changes are made the firmware in the safe modules has to be updated. To speed up the process a digital twin would be beneficial. This enables testing of parameters and formulation of criteria detecting faults. The purpose of the work is to develop a digital twin for steering and braking safe functions and evaluate the performance using data from machines as well as data from a HIL-rig. Also, the impact of the hydraulic model used in the HIL-rig is investigated. When the model is built two test cases are used to investigate how well the model replicates the behaviour of the real system and how sensitive it is to what input data is used. The biggest difference in the data is the sampling time, machine logs have 80 ms interval while logs from the rig are logged every 5 ms. It is discovered that some of the fault detection functions work very well no matter what data is used while others must have the better resolution to be trusted. The complexity of the hydraulic model used impacts the pressures but seem to have little effect on which fault codes are activated. With this the main purpose is partly achieved and further investigation is needed before the model can be used for all fault codes.

In the era of Industry 4 and Digital Twin – DT- (integrating Audio-Video, Virtual Reality, Augmented Reality and Haptics - from the Greek word Haptikos meaning "able to touch") and the Tactile Internet (TI), it becomes obvious that telecom stakeholders need different networks requirements to provision high quality services with respect to the new standards. In reality, this era is proposed as TI, and it will achieve a true paradigm shift from content delivery to skill-set delivery network types, thanks to recent technical breakthroughs. It will build a new internet structure with improved capabilities; but it will be difficult to meet the technical needs of the TI with current fourth generation (4G) mobile communication systems. As a result, 5G mobile communication systems will be used at the wireless edge and as a key enabler for TI due to its automated core network functionalities. Because of the COVID-19 outbreak, most daily activities such as employment, research, and education are now conducted online rather than in person. As a result, internet traffic has risen dramatically. Nowadays, Tactile Internet is in its infancy deployment phase worldwide. For this reason, and because of the growing need of its applications, the feasibility of these applications on the existing and deployed networks infrastructures, especially in the growing countries, is thought to be very hard, even quasi-impossible. Since 5G is not reaching yet its convergence stage (i.e. it is not deployed everywhere) and there is a huge stress on mobile communications given that the world is still facing the COVID-19 Pandemic, and since all the activities are taking place online, we propose design and implement a QoS framework to facilitate the feasibility and the applicability of the TI systems, where no 5G infrastructure is deployed. This framework will predict the most suitable network type to be deployed for certain given TI applications with certain given KPIs (Key Performance Indicators). Also, this framework is scalable, in such it gives an idea of even the future Next Generation Mobile Networks types (NGMN, if necessary). “To deal” with TI applications, means “to deal” with Haptics added to Audio and Video streams. Therefore, performance evaluation for haptic networks is required. And since there are different types of haptic networks, so interoperability is needed. Consequently, a standardization form is necessary for that purpose, to annotate and describe the haptic network. The first idea that flashes in mind, is the use of Ontologies. In these latters, we can add intelligent rules to infer additional data and predict resource requirements in order to achieve better performance. Many works in the research rely on Artificial Intelligence approaches to tackle the above-mentioned standardization, but very few depend on ontologies, and without futuristic outcomes, especially for the optimization problem. We mean by optimization, the optimal types, methods and rules that are able to accommodate the applicability of the TI systems (here come the applications KPIs) in an acceptable environment or infrastructure (here come the networking KPIs), and even-more, to infer the most optimal network type. To help manufacturing companies take full advantage of the TI, we propose to develop new methods and tools (ontologies) to intelligently handle the TI, DT (Digital Twin) and IoT (Internet of Things) sensor data and process data at the edge of the network and deliver faster insights. The outcomes of these ontologies, have been validated through two conducted case studies, where we simulated, in the first, TI traffic over Wi-Fi, WiMAX and UMTS (3G) infrastructures; While in the second we used 4G (LTE-A), along with SDN (Software Defined Networking) integrated to MEC (Mobile Edge Computing) as networking backbone. The results, in terms of QoS KPIs performance evaluation, present high relevance to our proposed Ontology outcomes.

This study aims to create a design concept for a digital twin to understand how it could be used to increase the health adherence of users through risk communication. This was done while also looking at how such a system could counteract potential health anxiety. The massive digitization and available data has enabled better opportunities to accurately represent and affect a person’s health in the form of a digital twin. The primary way of conducting the study was by using the ’Design Thinking’ method which incorporates five steps: Empathizing with the users’ needs, defining the problems, ideating, creating prototypes, and finally testing these. A literature study, four user interviews as well as two interviews with healthcare professionals were conducted to get a better understanding of what problems needed to be solved. The findings from these together with a brainstorming session resulted in low fidelity (LoFi) and high fidelity (HiFi) versions of a mobile prototype. A single overview page of a desktop version for health professionals was also created. The mobile prototypes were user tested, and input was asked from stakeholders and healthcare professionals regarding the risk communication and visualization via walkthroughs of the prototypes. The usability results of the tests were positive with the HiFi version scoring 83.5 / 100 on the System Usability Scale which measures usability, and this score is deemed to be ’good’. The risk communication used received positive feedback, and the findings showed that a digital twin could potentially help with adherence and prevention by the use of summaries, visualization, as well as combining icons with the use of absolute risk and frequencies. To minimize the risk of health anxiety, a digital twin could reduce health information that is not very serious or important through a ”less-is-more” approach. Other effective means could be to show positive visualization and by being mindful of the ordering of risks and benefits, showing the user the positive aspects after the negative ones. Despite this, because of the lower sample size and hypothetical test scenario, further studies need to be conducted to verify the validity in more real-life scenarios. More isolated testing should be done to understand the effects better, both in terms of risk communication and usability. Additional things that could be beneficial to look at could be the implementation of gamification elements in the digital twin, further development of a desktop version for healthcare staff, as well as using more personalization options.

Klimatförändring ställer idag krav på högre energieffektivitet vilket lett till utbyggnaden av ett distribuerat energisystem. Samtidigt introduceras framväxande teknologier som digitala tvillingar till det nya energisystemet i hopp om att ytterligare effektivisera systemet. För att främja samarbete mellan industrin och akademin, och således stödja utvecklingen och implementeringen av digitala tvillingar, bör aktörernas syner sammanföras. Syftet med arbetet är därav att undersöka ifall det finns några likheter och skillnader mellan industri och akademi i hur de uppfattar användningsområdena och utmaningarna med digitala tvillingar av distribuerade energisystem. För att besvara forskningsfrågan utfördes inledningsvis en systematisk litteraturstudie. Studien utgör arbetets underlag för akademins uppfattning om digitala tvillingars användningsområden och utmaningar. Vidare utfördes fem intervjuer med olika industriaktörer med insikt i digitala tvillingar och distribuerade energisystem för att avgöra deras uppfattning om teknologin. Insikterna från litteraturstudien och intervjuerna ställdes sedan mot varandra för att identifiera eventuella likheter och skillnader. De användningsområden som identifierades av akademin och industrin var simulering, felidentifiering och prediktivt underhåll, visualisering och styrning, cybersäkerhet, optimering av kraftnätet samt prognostisering och estimering. Utmaningarna som identifierades av akademin var standardiserade ramverk för modellering och för datahantering, brist på passande sensorer, datalagringsmöjligheter, datorers beräkningskapacitet och cyberattacker. Industrin identifierade motstånd till ny teknologi, kompetensbrist, silotänk, teknologins värdeskapande, datahantering och cyberattacker som huvudutmaningarna med digitala tvillingar. Utifrån analysen har industrin och akademin en liknande uppfattning om digitala tvillingars användningsområden inom distribuerade energisystem men uppfattningen om utmaningarna med digitala tvillingar var, inom akademin, mer teknikbaserad medan den inom industrin var främst icketeknisk. / Today, the increasing threat of climate change has created a greater need for higher energy efficiency, which has led to the development of a distributed energy system. At the same time, emerging technologies such as digital twins are being introduced into the new energy system in the hope of further improving the efficiency of the system. To promote cooperation between industry and academia, and thus support the development and implementation of digital twins, the views of the actors should be brought together. The purpose of this work is therefore to investigate whether there are any similarities and differences between industry and academia in how they perceive the applications and challenges of digital twins of distributed energy systems.  To answer the research question, a systematic literature study was initially conducted. The study constitutes the basis for the academia's perception of the use cases and challenges of digital twins. Furthermore, five interviews were conducted with different industrial actors with insight into digital twins and distributed energy systems to determine their perception of the technology. The insights from the literature study and interviews were then compared to identify any similarities and differences.  The application areas identified by academia and industry were simulation, fault identification and predictive maintenance, visualization and control, cyber security, grid optimization, and forecasting and estimation.  The challenges identified by academia were standardized modelling and data management frameworks, lack of suitable sensors, data storage capabilities, computational capacity of computers and cyber-attacks. Industry identified resistance to new technologies, skills shortages, silo thinking, technology value creation, data management and cyber-attacks as the main challenges of digital twins. Based on the analysis, industry and academia have a similar perception of the use cases of digital twins of distributed energy systems but the perception of the challenges of digital twins was, in academia, more technology-based while in industry it was mainly non-technical.

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The dexterity of computer systems to resemble and mimic human intelligence is artificial intelligence. Artificial intelligence has reformed the diagnostic and therapeutic precision and competence in various fields of medicine. Artificial intelligence appears to play a bright role in medical diagnosis. Computer systems using artificial intelligence help in the assessment of medical images and enormous data. This research aims to identify how artificial intelligence-based technology is reforming the art of medicine. Artificial intelligence empowers providers in improving efficiency and overall healthcare. Newer machine learning techniques lead the automatic diagnostic systems. Areas of medicine such as medical imaging, automated clinical decision-making support have made significant advances with respect to artificial intelligence technology. With improved diagnosis and prognosis, artificial intelligence possesses the capability to revolutionize various fields of medicine. Artificial intelligence has its own limitations and cannot replace a bedside clinician. In the evolving modern medical digital world, physicians need to support artificial intelligence rather than fear it replacing trained physicians for improved healthcare.

In applications spanning across aerospace, marine, automotive, energy, and space travel domains, composite materials have become ubiquitous because of their superior stiffness-to-weight ratios as well as corrosion and fatigue resistance. However, from a manufacturing perspective, these advanced materials have introduced new challenges that demand the development of new tools. Due to the complex anisotropic and nonlinear material properties, composite materials are more difficult to model than conventional materials such as metals and plastics. Furthermore, there exist ultra-high precision requirements in safety critical applications that are yet to be reliably met in production. Towards developing new tools addressing these challenges, this dissertation aims to (i) build high-fidelity numerical simulations of composite assembly processes, (ii) bridge these simulations to machine learning tools, and (iii) apply data-driven solutions to process control problems while identifying and overcoming their shortcomings. This is accomplished in case studies that model the fixturing, shape control, and fastening of composite fuselage components. Therein, simulation environments are created that interact with novel implementations of modified proximal policy optimization, based on a newly developed reinforcement learning algorithm. The resulting reinforcement learning agents are able to successfully address the underlying optimization problems that underpin the process and quality requirements. / Doctor of Philosophy / Within the manufacturing domain, there has been a concerted effort to transition towards Industry 4.0. To a large degree, this term refers Klaus Schwab's vision presented at the World Economic Forum in 2015, in which he outlined fundamental systemic changes that would incorporate ubiquitous computing, artificial intelligence (AI), big data, and the internet-of-things (IoT) into all aspects of productive activities within the economy. Schwab argues that rapid change will be driven by fusing these new technologies in existing and emerging applications. However, this process has only just begun and there still exist many challenges to realize the promise of Industry 4.0. One such challenge is to create computer models that are not only useful during early design stages of a product, but that are connected to its manufacturing processes, thereby guiding and informing decisions in real-time. This dissertation explores such scenarios in the context of composite structure assembly in aerospace manufacturing. It aims to link computer simulations that characterize the assembly of product components with their physical counterparts, and provides data-driven solutions to control problems that cannot typically be solved without tedious trial-and-error approaches or expert knowledge.

Digital twin is an emerging technology that enhances digital transformation across many industries and domains. Most digital twins are made for a work context, and end users are the domain experts who carry knowledge in the work processes and products of which digital twin is part. The research gap for the present study is found in the missing adoption of a user-centered design approach and systematic evaluation of digital twins from the perspective of end users. User-Centered Design is a well-known design philosophy that engages users in the design process. By involving users, designers can better understand users and create situations where users can introduce their knowledge, needs and concerns into the products and systems. Emerging research questions for this study are: RQ1: What insights could be obtained with user-centered design and user involvement for the design of digital twin? RQ2: What limitations could user-centered design and user involvement incorporate in the design process of digital twins? This study will use both previous studies and empirical data from a scenario-based approach, workshops, observation, and interviews. Further, it will explore a theoretical framework combining User-Centered Design and Activity theory. This study aims to investigate what knowledge we can gain with users in focus and how that might help to fill the knowledge gap of previous research about user-centered involvement.