Die Verbindung von Robotern mit Virtual Reality (VR) zur Echtzeitvisualisierung stellt eine erhebliche Programmierherausforderung dar. Dieser Vortrag zeigt einen vereinfachten Ansatz unter Verwendung des Robot Operating System (ROS), einer Open-Source-Plattform, die diese Aufgabe erleichtert. Durch den Einsatz von ROS kann der Programmieraufwand deutlich reduzieren werden, indem vorhandene Pakete für eine nahtlose Integration von Robotern und VR genutzt werden. In dieser Präsentation wird schrittweise erläutert, wie diese Verbindung realisiert wird, was neue Möglichkeiten in der Visualisierung und Steuerung von Robotern mit minimalem Programmieraufwand erschließt. Diese Methode ebnet den Weg für innovative Anwendungen in Robotik und VR und bietet praktische Einblicke für Entwickler und Forscher. / Connecting robots with Virtual Reality (VR) for real-time visualization poses a significant programming challenge. This presentation demonstrates a simplified approach using the Robot Operating System (ROS), an open-source platform that facilitates this task. By utilizing ROS, the programming effoit can be significantly reduced by leveraging existing packages for seamless robot-VR integration. This presentation will explain step-by-step how this connection can be realized, opening new possibilities in visualization and control of robots with minimal programming effort. This method paves the way for innovative applications in robotics and VR, providing practical insights for developers and researchers.

Background. In today’s fast-paced business world, there is a notable shift from product-centric to solution-centric approaches driven by discussions around sustainability. This shift underscores the increasing demand for Product-Service systems as companies strive to adapt to evolving customer needs. Digital Twin-based approaches have emerged as a potential tool in this landscape, providing new methods for gathering customer insights. The construction industry is a crucial sector vital to economic growth, accounting for approximately 10 percent of the gross domestic product of many countries. However, it faces several challenges, including low productivity, unpredictability, and slow innovation. Objectives. The aim of this thesis is to propose a system that improves through-life support in heavy construction equipment. Additionally, the potential benefit of utilizing a Digital Twin for the development of Product-Service Systems will be suggested based on the developed system. Methods. In this thesis, the design approach was chosen to be Design Thinking to provide a structured framework that fits the uncertain and iterative process that the project demands. Furthermore, the tools and methods from Design Thinking were utilized to ensure the final solution was developed with creative support and constant concept feedback to address the user’s needs. Results. This thesis results in three potential areas of improvement in the through-life support of construction equipment, concepts that could address these, and the problem that is stopping their realization. Furthermore, a proposed solution to this problem has been developed that could enable the implementation of Digital Twins in construction equipment. Conclusions. This thesis finds that data collection issues prevent the implementation of Digital Twins in construction equipment. It also presents several potential strengths and weaknesses of Digital Twins in Product-Service System development.Additionally, it presents some future directions in Digital Twins and Product-Service Systems that need further work. / Bakgrund. I dagens snabba och skiftande affärsvärld sker en märkbar flytt från produktcentrerade till lösning-centrerade tillvägagångssätt, drivna av diskussioner kring hållbarhet. Denna förändring framhäver den ökande efterfrågan på Produkt-Tjänstesystem för företag som strävar efter att anpassa sig till det ändrande kundbehovet. Digital Tvilling-baserade tillvägagångssätt har framträtt som ett potentiellt verktyg i detta sammanhang, och erbjuder nya metoder för att samla kunskap om kunderna. Byggindustrin är en avgörande sektor för ekonomisk tillväxt och står för cirka 10 procent av många länders bruttonationalprodukt. Dock står den inför flera utmaningar som låg produktivitet, oförutsägbarhet och långsam innovation. Syfte. Syftet med detta examensarbete är att föreslå ett system som förbättrar service genom hela livscykeln för anläggningsmaskiner. Dessutom kommer de potentiella fördelarna med att använda en Digital Tvilling för utvecklingen av Produkt- Tjänstesystem att föreslås baserat på det utvecklade systemet. Metod. I detta arbete valdes designmetoden Design Thinkin för att tillhandahålla en strukturerad ram som passar den osäkra och iterativa processen som projektet kräver. Dessutom användes verktyg och metoder från Design Thinking för att säkerställa att den slutliga lösningen utvecklades med kreativt stöd och konstant konceptfeedback för att vara riktat mot användarens behov. Resultat. Examensarbetet resulterar i tre potentiella förbättringsområden inom service genom hela livscykeln för anläggningsmaskiner, koncept som kan adressera dessa och det problem som hindrar deras förverkligande. Dessutom har en föreslagen lösning på detta problem utvecklats som kan möjliggöra implementeringen av Digitala Tvillingar i anläggningsmaskiner. Slutsatser. Arbetet konstaterar att problem med datainsamling förhindrar implementeringen av Digitala Tvillingar i anläggningsmaskiner. Det presenterar också flera potentiella styrkor och svagheter hos Digitala Tvillingar i utvecklingen av Produkt-Tjänstesystem. Dessutom presenteras några områden inom Digitala Tvillingar och Produkt-Tjänstesystem som behöver ytterligare arbete.

Die Nutzung von Augmented Reality (AR) stellt eine Vielzahl von Lösungsansätzen für Herausforderungen unterschiedlicher Bereiche, z.B. der Industrie, Medizin, Unterhaltungsmedien und Bildung, zur Verfügung. Speziell werden hier die Möglichkeiten von AR in der Fertigungsindustrie, genauer bei der Abnahme elektrischer Antriebe der Siemens AG, betrachtet. Dabei werden unter anderem messbare Größen wie Drehmoment, Ankerstrom, -spannung, Drehzahl, Schwingungen, Fertigungstoleranzen etc. gemessen, aber auch nicht quantifizierbare Größen wie Sichtprüfungen von Schweißnähten und Lackierung in Betracht gezogen. Angestrebt wird eine Methode, welche es zukünftig ermöglicht, die Inbetriebnahme ortsunabhängig zu verfolgen und Inspektionen aus der Ferne durchzuführen. Die Herausforderung liegt dabei darin, eine zumindest gleichwertige, wenn nicht sogar verbesserte Erfahrung und Prüfergebnisvalidität für die Beteiligten gegenüber der vor Ort Abnahme zu erzeugen. Im Rahmen des Forschungsvorhabens wurde in interdisziplinärer Zusammenarbeit zwischen Ingenieur/-innen und Sozialwissenschaftler/-innen ein Demonstrator-Konzept für eine ortsunabhängige Maschinenabnahme entwickelt.

Virtualization of products means the representation of some of their properties by models. In a stronger digitalized world, these models will gain a much broader use than models had in engineering so far. Even for one modelling aspect different models of the same product will be used, depending on the specific need of the model user. That need may change in the course of product life, between first product concepts till over the different phases of development, to product use, maintenance, or even recycling. Since a digitalized world use of these diverse models will not be limited to experts model consistency will play a much stronger role. Model hierarchies will play a stronger role and can serve also as means for teaching product users a deeper understanding of product properties. A consistent model hierarchy leading from a simple to a more advanced property representation can support this learning process. In this paper perturbation methods are analyzed as a means for setting up model hierarchies in a consistent manner. This is studied by models for the behavior of a electrohydraulic drive, which consists of a variable speed motor, a pump, a double stroke cylinder and a counterbalance valve. Model hierarchy is achieved by model reduction in the sense of perturbation theory. The use of these different models for different questions in a system design context and their interrelations are exemplified.

Over the last few decades, the complexity and variety of automation systems have increased dramatically. Commissioning has grown more and more critical for the entire industry. Conventional commissioning is time-consuming and expensive. It's always been a challenge in manufacturing to put new designs into production or implement new technologies, control codes, or tactics. In Virtual Commissioning (VC), control programs of the physical system's Digital Twin (DT) can be validated in Software-in-the-Loop (SIL) before the actual commissioning. The emergence of new VC tools and methods has become a tremendous advantage, bringing the values of shorter duration, flexibility, and lower risks to the commissioning process. In this thesis, advanced process control was developed using the software Matlab and Simulink in conjunction with the engineering tools S7-PLCSIM Advanced and STEP 7 TIA Portal to conduct VC. A VC approach with four key steps is taken to evaluate the possibility of validating advanced process control. The steps are modeling DT of a rolling mill, model-based control design, simulation model development in Simulink, communication between the simulation model and the PLC program using S-7 TIA Portal, and PLCSIM Advanced. Also, a simulated Human-Machine Interface was designed to operate and visualize the process. VC of the rolling mill process was verified and validated by Model-in-the-Loop (MIL) and SIL simulation. The simulation gives satisfactory results as both MIL and SIL show identical outputs of the process.

Our society moves towards digitalization and the industry is not an exception. Siemenshas developed a wireless condition monitoring device called Simotics Connect in order tohelp them to move forward in the world of digitalization. The Simotics Connect has threeinbuilt sensors. One for temperature, one for vibrations and one for magnetic flux density,a product that is new in the market. This master thesis has investigated its usability forthird party motors, which has not been done.Four areas were investigated, the status in the current market, creating a motorgeometry estimation based on nameplate data, presenting a temperature model to calculatea motor’s cross section temperature and, finally, proposed a stator current model using themagnetic field measurement.Market research has shown that a space for the Simotics Connect to thrive in mostdefinitely exists.The motor geometry estimation, that is based on preliminary electromagnetic sizing,creates a digital twin for the motor that has sufficient accuracy as a tool when calculatinge.g. temperature calculations but lacks accuracy for more advanced and sensitivecalculations e.g for magnetic flux density measurement usability.The temperature model that is presented shows great accuracy when calculating thecross section temperature in the stator but the accuracy decreases for the cross sectiontemperature in the rotor.A stator current model is proposed using a proportional relationship between themagnetic flux density and stator current. The results indicates a linear relationship, thoughusing the digital twin to calculate the proportional constant were concluded to not beaccurate enough. / Sammhället rör sig idag mot digitalisering och industrin är ej ett undantag. Siemens harutvecklat en trådlös underhållsmätare kallad Simotics Connect för att hjälpa dem strävamot en värld inom digitalisering. Simotics Connect hat tre inbyggda sensorer. En för temperatur,en för vibrationer och en för magnetisk flödestäthet, vilket är nytt på marknaden.Detta masterprojekt har undersökt användningen av Simotics Connect för tredjepartsmotorer,vilket ej har gjorts tidigare.Fyra områden undersöktes, statusen på den nuvarande marknaden, en motorgeometriuppskattningmodellbaserad på namnskylsdata, en temperaturmodell för att beräknamotorns tvärsnittstemperatur och, slutligen, en statorströmmodell som använder sig avmagnetiska flödestäthetsmätningen.Marknadsundersökningen har visat att det finns ett utrymme för Simotics Connectatt blomstra inom på den nuvarande marknaden.Motorns geometriska uppskattning, som är baserad i preliminär elektromagnetiskgeometribestämning, skapar en digital tvilling av motorn som är tillräckligt noggrann föratt aggera som ett verktyg vid t.ex. temperatursberäkningar men saknar noggrannhet förmer avancerade och känsliga beräkningar, t ex för användbarhet inom magnetisk flödestäthetsberäkningar.Temperaturmodellen som presenteras visar stor noggrannhet vid beräkning av statornstvärsnittstemperatur, men noggrannheten minskar för rotorns tvärsnittstemperatur.En statorströmmodell föreslås med ett proportionellt förhållande mellan magnetflödesdensitetenoch statorströmmen. Resultaten indikerar ett linjärt förhållande, men användandetav den digitala tvillingen för att beräkna proportionell konstant konstateras attinte vara tillräckligt noggrann metod.

<p>A procedure for calibrating a discrete element (DE) computational soil model for various moisture contents using a conventional Asperity-Spring friction modeling technique is presented in this thesis. The procedure is based on the outcomes of two physical soil experiments:</p> <p>(1) Compression and (2) unconfined shear strength at various levels of normal stress and normal pre-stress. The Compression test is used to calibrate the DE soil plastic strain and elastic strain as a function of Compressive stress. To calibrate the DE inter-particle friction coefficient and adhesion stress as a function of soil plastic strain, the unconfined shear test is used. This thesis describes the experimental test devices and test procedures used to perform the physical terramechanical experiments. The calibration procedure for the DE soil model is demonstrated in this thesis using two types of soil: sand-silt (2NS Sand) and silt-clay(Fine Grain Soil) over 5 different moisture contents: 0%, 4%, 8%, 12%, and 16%. The DE based models response are then validated by comparing them to experimental pressure-sinkage results for circular disks and cones for those two types of soil over 5 different moisture contents. The Mean Absolute  Percentage Error (MAPE) during the compression calibration was 26.9% whereas during the unconfined shear calibration, the MAPE was calculated to be 11.38%. Hence, the overall MAPE was calculated to be 19.34% for the entire calibration phase.</p>

Tesis por compendio / [ES] El paradigma de la Industria 4.0 (I4.0) gravita en gran medida sobre el potencial de las tecnologías de la información y la comunicación (TIC) para mejorar la competitividad y sostenibilidad de las industrias. El concepto de Smart Manufacturing Scheduling (SMS) surge y se inspira de ese potencial. SMS, como estrategia de transformación digital, aspira a optimizar los procesos industriales mediante la aplicación de tecnologías como el gemelo digital o digital twin (DT), el modelo de gestión zero-defect manufacturing (ZDM), y el aprendizaje por refuerzo profundo o deep reinforcement learning (DRL), con el propósito final de orientar los procesos de programación de operaciones hacia una automatización adaptativa en tiempo real y una reducción de las perturbaciones en los sistemas de producción. SMS se basa en cuatro principios de diseño del espectro I4.0: automatización, autonomía, capacidad de acción en tiempo real e interoperabilidad. A partir de estos principios clave, SMS combina las capacidades de la tecnología DT para simular, analizar y predecir; la del modelo ZDM para prevenir perturbaciones en los sistemas de planificación y control de la producción; y la del enfoque de modelado DRL para mejorar la toma de decisiones en tiempo real. Este enfoque conjunto orienta los procesos de programación de operaciones hacia una mayor eficiencia y, con ello, hacia un mayor rendimiento y resiliencia del sistema productivo. Esta investigación emprende, en primer lugar, una revisión exhaustiva del estado del arte sobre SMS. Con la revisión efectuada como referencia, la investigación plantea un modelo conceptual de SMS como estrategia de transformación digital en el contexto del proceso de programación del taller de trabajos o job shop. Finalmente, la investigación propone un modelo basado en DRL para abordar la implementación de los elementos clave del modelo conceptual: el DT del taller de trabajos y el agente programador. Los algoritmos que integran este modelo se han programado en Python y han sido validados contra varias de las más conocidas reglas heurísticas de prioridad. El desarrollo del modelo y los algoritmos supone una contribución académica y gerencial en el área de la planificación y control de la producción. / [CA] El paradigma de la Indústria 4.0 (I4.0) gravita en gran mesura sobre el potencial de les tecnologies de la informació i la comunicació (TIC) per millorar la competitivitat i la sostenibilitat de les indústries. El concepte d'smart manufacturing scheduling (SMS) sorgeix i inspira a partir d'aquest potencial. SMS, com a estratègia de transformació digital, aspira a optimitzar els processos industrials mitjançant l'aplicació de tecnologies com el bessó digital o digital twin (DT), el model de gestió zero-defect manufacturing (ZDM), i l'aprenentatge per reforçament profund o deep reinforcement learning (DRL), amb el propòsit final dorientar els processos de programació doperacions cap a una automatització adaptativa en temps real i una reducció de les pertorbacions en els sistemes de producció. SMS es basa en quatre principis de disseny de l'espectre I4.0: automatització, autonomia, capacitat d¿acció en temps real i interoperabilitat. A partir d'aquests principis clau, SMS combina les capacitats de la tecnologia DT per simular, analitzar i predir; la del model ZDM per prevenir pertorbacions en els sistemes de planificació i control de la producció; i la de de l'enfocament de modelatge DRL per millorar la presa de decisions en temps real. Aquest enfocament conjunt orienta els processos de programació d'operacions cap a una eficiència més gran i, amb això, cap a un major rendiment i resiliència del sistema productiu. Aquesta investigació emprèn, en primer lloc, una exhaustiva revisió de l'estat de l'art sobre SMS. Amb la revisió efectuada com a referència, la investigació planteja un model conceptual de SMS com a estratègia de transformació digital en el context del procés de programació del taller de treballs o job shop. Finalment, la investigació proposa un model basat en DRL per abordar la implementació dels elements claus del model conceptual: el DT del taller de treballs i l'agent programador. Els algorismes que integren aquest model s'han programat a Python i han estat validats contra diverses de les més conegudes regles heurístiques de prioritat. El desenvolupament del model i els algorismes suposa una contribució a nivell acadèmic i gerencial a l'àrea de la planificació i control de la producció. / [EN] The Industry 4.0 (I4.0) paradigm relies, to a large extent, on the potential of information and communication technologies (ICT) to improve the competitiveness and sustainability of industries. The smart manufacturing scheduling (SMS) concept arises and draws inspiration from this potential. As a digital transformation strategy, SMS aims to optimise industrial processes through the application of technologies, such as the digital twin (DT), the zero-defect manufacturing (ZDM) management model and deep reinforcement learning (DRL), for the ultimate purpose of guiding operations scheduling processes towards real-time adaptive automation and to reduce disturbances in production systems. SMS is based on four design principles of the I4.0 spectrum: automation, autonomy, real-time capability and interoperability. Based on these key principles, SMS combines the capabilities of the DT technology to simulate, analyse and predict; with the ZDM model, to prevent disturbances in production planning and control systems; by the DRL modelling approach, to improve real-time decision making. This joint approach orients operations scheduling processes towards greater efficiency and, with it, a better performing and more resilient production system. This research firstly undertakes a comprehensive review of the state of the art on SMS. By taking the review as a reference, the research proposes a conceptual model of SMS as a digital transformation strategy in the job shop scheduling process context. Finally, it proposes a DRL-based model to address the implementation of the key elements of the conceptual model: the job shop DT and the scheduling agent. The algorithms that integrate this model have been programmed in Python and validated against several of the most well-known heuristic priority rules. The development of the model and algorithms is an academic and managerial contribution in the production planning and control area. / This thesis was developed with the support of the Research Centre on Production Management and Engineering (CIGIP) of the Universitat Politècnica de València and received funding from: the European Union H2020 programme under grant agreement No. 825631, “Zero Defect Manufacturing Platform (ZDMP)”; the European Union H2020 programme under grant agreement No. 872548, "Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs (DIH4CPS)"; the European Union H2020 programme under grant agreement No. 958205, “Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)”; the European Union Horizon Europe programme under grant agreement No. 101057294, “AI Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability and Resilience” (AIDEAS); the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-101344-B-I00, "Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)"; the Valencian Regional Government, in turn funded from grant RTI2018- 101344-B-I00 by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, "Industrial Production and Logistics optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/2021/065); and the grant PDC2022-133957- I00, “Validation of transferable results of optimisation of zero-defect enabling production technologies for supply chain 4.0” (CADS4.0-II) funded by MCIN/AEI/10.13039/501100011033 and by European Union Next GenerationEU/PRTR. / Serrano Ruiz, JC. (2024). Job shop smart manufacturing scheduling by deep reinforcement learning for Industry 4.0 [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202871 / Compendio

<p>  </p> <p>A <em>digital twin</em> (DT), which keeps track of nuclear reactor history to provide real-time predictions, has been recently proposed for nuclear reactor monitoring. A digital twin can be implemented using either a differential equations-based physics model, or a data-driven machine learning model<strong>. </strong>The principal challenge in physics model-based DT consists of achieving sufficient model fidelity to represent a complex experimental system, while the main challenge in data-driven DT appears in the extensive training requirements and potential lack of predictive ability. </p> <p>In this thesis, we investigate the performance of a hybrid approach, which is based on physics-informed neural networks (PINNs) that encode fundamental physical laws into the loss function of the neural network. In this way, PINNs establish theoretical constraints and biases to supplement measurement data and provide solution to several limitations of purely data-driven machine learning (ML) models. We develop a PINN model to solve the point kinetic equations (PKEs), which are time dependent stiff nonlinear ordinary differential equations that constitute a nuclear reactor reduced-order model under the approximation of ignoring the spatial dependence of the neutron flux. PKEs portray the kinetic behavior of the system, and this kind of approach is the basis for most analyses of reactor systems, except in cases where flux shapes are known to vary with time. This system describes the nuclear parameters such as neutron density concentration, the delayed neutron precursor density concentration and reactivity. Both neutron density and delayed neutron precursor density concentrations are the vital parameters for safety and the transient behavior of the reactor power. </p> <p>The PINN model solution of PKEs is developed to monitor a start-up transient of the Purdue University Reactor Number One (PUR-1) using experimental parameters for the reactivity feedback schedule and the neutron source. The facility under modeling, PUR-1, is a pool type small research reactor located in West Lafayette Indiana. It is an all-digital light water reactor (LWR) submerged into a deep-water pool and has a power output of 10kW. The results demonstrate strong agreement between the PINN solution and finite difference numerical solution of PKEs. We investigate PINNs performance in both data interpolation and extrapolation. </p> <p>The findings of this thesis research indicate that the PINN model achieved highest performance and lowest errors in data interpolation. In the case of extrapolation data, three different test cases were considered, the first where the extrapolation is performed in a five-seconds interval, the second where the extrapolation is performed in a 10-seconds interval, and the third where the extrapolation is performed in a 15-seconds interval. The extrapolation errors are comparable to those of interpolation predictions. Extrapolation accuracy decreases with increasing time interval.</p>

The transportation industry stands for a big chunk of the worlds total carbon emissions. To counter this problem electric vehicles are seen as a good solution. However, these vehicles come at a greater cost and do not offer the same range as their less environmentally friendly counterpart. To lessen costs and development time when optimizing electric vehicles, simulations of the vehicles functionality can be utilized. One way of getting such simulations is to design a digital twin of the physical system. A digital twin is able to mimic the functionality of the physical system and can therefore offer well based indications of how a change in design will change the performance in reality. In this thesis a digital twin of the cooling system of an electric boat is designed with realistic results. Cooling systems in the scope of electric vehicles are of grave importance since the electric driveline becomes hot during use which can hinder performance of the vehicle. This is especially true for the high voltage batteries that tend to have quite a narrow range of temperatures within which performance is optimal. This thesis handles an attempt at optimizing the cooling system, replicated by the digital twin, by the use of a temperature predictive model. Three different machine learning models were tested and the resulting best model achieved a mean absolute error of 2.4 and a mean average percentage error of 5.7. However, the model was unable to foresee sudden temperature spikes and drops. A possible fix, that could not be tested in this thesis, would be to implement further input data such as driver profiles and/or GPS data with speed limits. / Transportindustrin står för en stor del av världens totala koldioxidutsläpp. För att motverka detta problem ses elfordon som en bra lösning. Dessa fordon kommer dock till en högre kostnad och erbjuder inte samma räckvidd som deras mindre miljövänliga motpart. För att minska kostnader och utvecklingstid vid optimering av elfordon kan simuleringar av fordonens funktionalitet användas. Ett sätt att få sådana simuleringar är att designa en digital tvilling av det fysiska systemet. En digital tvilling kan efterlikna det fysiska systemets funktionalitet och kan därför erbjuda välbaserade indikationer på hur en förändring i design kommer att förändra prestandan. I detta examensarbete designas en digital tvilling av kylsystemet i en elbåt med realistiska resultat. Kylsystem i elfordon är av stor betydelse eftersom den elektriska drivlinan blir varm under användning, vilket kan hindra fordonets prestanda. Detta gäller särskilt för högspänningsbatterierna som tenderar att ha ett ganska smalt temperaturintervall för optimal prestanda. Denna avhandling behandlar ett försök att optimera kylsystemet, replikerat av den digitala tvillingen, genom att använda en temperaturförutsende modell. Tre olika maskininlärningsmodeller testades och den resulterande bästa modellen uppnådde ett genomsnittligt absolut fel på 2.4 och ett genomsnittligt procentuellt fel på 5.7. Modellen kunde dock inte förutse plötsliga temperaturspikar och -fall. En möjlig fix, som inte kunde testas i denna avhandling, skulle vara att implementera ytterligare indata såsom förarprofiler och/eller GPS-data med hastighetsbegränsningar.