Thematische Bibliographien / Digital Twin Technology

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Auswahl der wissenschaftlichen Literatur zum Thema „Digital Twin Technology“

Autor: Grafiati

Veröffentlicht am 29. Juni 2021

Zuletzt aktualisiert am 11. Februar 2022

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Zeitschriftenartikel zum Thema "Digital Twin Technology"

Madni, Azad, Carla Madni und Scott Lucero. „Leveraging Digital Twin Technology in Model-Based Systems Engineering“. Systems 7, Nr. 1 (30.01.2019): 7. http://dx.doi.org/10.3390/systems7010007.

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Digital twin, a concept introduced in 2002, is becoming increasingly relevant to systems engineering and, more specifically, to model-based system engineering (MBSE). A digital twin, like a virtual prototype, is a dynamic digital representation of a physical system. However, unlike a virtual prototype, a digital twin is a virtual instance of a physical system (twin) that is continually updated with the latter’s performance, maintenance, and health status data throughout the physical system’s life cycle. This paper presents an overall vision and rationale for incorporating digital twin technology into MBSE. The paper discusses the benefits of integrating digital twins with system simulation and Internet of Things (IoT) in support of MBSE and provides specific examples of the use and benefits of digital twin technology in different industries. It concludes with a recommendation to make digital twin technology an integral part of MBSE methodology and experimentation testbeds.

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August, Urban. „Digital Twin Technology for More Efficiency“. ATZproduction worldwide 6, Nr. 1 (März 2019): 54. http://dx.doi.org/10.1007/s38312-019-0012-0.

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Neethirajan, Suresh, und Bas Kemp. „Digital Twins in Livestock Farming“. Animals 11, Nr. 4 (03.04.2021): 1008. http://dx.doi.org/10.3390/ani11041008.

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Artificial intelligence (AI), machine learning (ML) and big data are consistently called upon to analyze and comprehend many facets of modern daily life. AI and ML in particular are widely used in animal husbandry to monitor both the animals and environment around the clock, which leads to a better understanding of animal behavior and distress, disease control and prevention, and effective business decisions for the farmer. One particularly promising area that advances upon AI is digital twin technology, which is currently used to improve efficiencies and reduce costs across multiple industries and sectors. In contrast to a model, a digital twin is a digital replica of a real-world entity that is kept current with a constant influx of data. The application of digital twins within the livestock farming sector is the next frontier and has the potential to be used to improve large-scale precision livestock farming practices, machinery and equipment usage, and the health and well-being of a wide variety of farm animals. The mental and emotional states of animals can be monitored using recognition technology that examines facial features, such as ear postures and eye white regions. Used with modeling, simulation and augmented reality technologies, digital twins can help farmers to build more energy-efficient housing structures, predict heat cycles for breeding, discourage negative behaviors of livestock, and potentially much more. As with all disruptive technological advances, the implementation of digital twin technology will demand a thorough cost and benefit analysis of individual farms. Our goal in this review is to assess the progress toward the use of digital twin technology in livestock farming, with the goal of revolutionizing animal husbandry in the future.

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Feder, Judy. „Will This Be the Decade of Full Digital Twins for Well Construction?“ Journal of Petroleum Technology 73, Nr. 03 (01.03.2021): 34–37. http://dx.doi.org/10.2118/0321-0034-jpt.

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The time needed to eliminate complications and accidents accounts for 20–25% of total well construction time, according to a 2020 SPE paper (SPE 200740). The same paper notes that digital twins have proven to be a key enabler in improving sustainability during well construction, shrinking the carbon footprint by reducing overall drilling time and encouraging and bringing confidence to contactless advisory and collaboration. The paper also points out the potential application of digital twins to activities such as geothermal drilling. Advanced data analytics and machine learning (ML) potentially can reduce engineering hours up to 70% during field development, according to Boston Consulting Group. Increased field automation, remote operations, sensor costs, digital twins, machine learning, and improved computational speed are responsible. It is no surprise, then, that digital twins are taking on a greater sense of urgency for operators, service companies, and drilling contractors working to improve asset and enterprise safety, productivity, and performance management. For 2021, digital twins appear among the oil and gas industry’s top 10 digital spending priorities. DNV GL said in its Technology Outlook 2030 that this could be the decade when cloud computing and advanced simulation see virtual system testing, virtual/augmented reality, and machine learning progressively merge into full digital twins that combine data analytics, real-time, and near-real-time data for installations, subsurface geology, and reservoirs to bring about significant advancements in upstream asset performance, safety, and profitability. The biggest challenges to these advancements, according to the firm, will be establishing confidence in the data and computational models that a digital twin uses and user organizations’ readiness to work with and evolve alongside the digital twin. JPT looked at publications from inside and outside the upstream industry and at several recent SPE papers to get a snapshot of where the industry stands regarding uptake of digital twins in well construction and how the technology is affecting operations and outcomes. Why Digital Twins Gartner Information defines a digital twin as a digital representation of a real-world entity or system. “The implementation of a digital twin,” Gartner writes, “is an encapsulated software object or model that mirrors a unique physical object, process, organization, person or other abstraction.” Data from multiple digital twins can be aggregated for a composite view across several real-world entities and their related processes. In upstream oil and gas, digital twins focus on the well—and, ultimately, the field—and its lifecycle. Unlike a digital simulation, which produces scenarios based on what could happen in the physical world but whose scenarios may not be actionable, a digital twin represents actual events from the physical world, making it possible to visualize and understand real-life scenarios to make better decisions. Digital well construction twins can pertain to single assets or processes and to the reservoir/subsurface or the surface. Ultimately, when process and asset sub-twins are connected, the result is an integrated digital twin of the entire asset or well. Massive sensor technology and the ability to store and handle huge amounts of data from the asset will enable the full digital twin to age throughout the life-cycle of the asset, along with the asset itself (Fig. 1).

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Steindl, Gernot, Martin Stagl, Lukas Kasper, Wolfgang Kastner und Rene Hofmann. „Generic Digital Twin Architecture for Industrial Energy Systems“. Applied Sciences 10, Nr. 24 (13.12.2020): 8903. http://dx.doi.org/10.3390/app10248903.

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Digital Twins have been in the focus of research in recent years, trying to achieve the vision of Industry 4.0. In the domain of industrial energy systems, they are applied to facilitate a flexible and optimized operation. With the help of Digital Twins, the industry can participate even stronger in the ongoing renewable energy transition. Current Digital Twin implementations are often application-specific solutions without general architectural concepts and their structures and namings differ, although the basic concepts are quite similar. For this reason, we analyzed concepts, architectures, and frameworks for Digital Twins in the literature to develop a technology-independent Generic Digital Twin Architecture (GDTA), which is aligned with the information technology layers of the Reference Architecture Model Industry 4.0 (RAMI4.0). This alignment facilitates a common naming and understanding of the proposed architectural structure. A proof-of-concept shows the application of Semantic Web technologies for instantiating the proposed GDTA for a use case of a Packed-Bed Thermal Energy Storage (PBTES).

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Anderl, Reiner, Sebastian Haag, Klaus Schützer und Eduardo Zancul. „Digital twin technology – An approach for Industrie 4.0 vertical and horizontal lifecycle integration“. it - Information Technology 60, Nr. 3 (01.07.2018): 125–32. http://dx.doi.org/10.1515/itit-2017-0038.

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Abstract Digital Twin technology is increasingly gaining importance for digitizing industry. Even if digital twin technology still needs fundamental research, its significance for industry has become very visible, as digital twin technology is a key success factor to professionalize Cyber-Physical Systems (CPS) applications. Industrie 4.0 as an initiative to increase industrial added value is based on establishing connectivity between CPS and to enable communication between CPS. The industrial application scenarios for Industrie 4.0 aim at vertical and horizontal lifecycle integration concepts where digital twin technology plays an important role. This contribution explains major concepts of Industrie 4.0 and derives the role of digital twin technology. Furthermore, digital twin approaches are presented and as well as the proposal to use the STEP-technology (Standard for the Exchange of Product Model Data, ISO 10303) as a fundamental basis for a comprehensive digital twin technology.

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Liao, Min, Guillaume Renaud und Yan Bombardier. „Airframe digital twin technology adaptability assessment and technology demonstration“. Engineering Fracture Mechanics 225 (Februar 2020): 106793. http://dx.doi.org/10.1016/j.engfracmech.2019.106793.

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Rodionov, Nikita, und Lyudmila Tatarnikova. „Digital twin technology as a modern approach to quality management“. E3S Web of Conferences 284 (2021): 04013. http://dx.doi.org/10.1051/e3sconf/202128404013.

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The concept of a digital twin and its types are discussed in this paper. The essence of the development of digital twins in the SysML language, the use of AnyLogic (simulation software) and the use of MES (Manufacturing Execution Systems) software for communication with production systems are described. The functions of neural technologies that can be integrated into a modern QMS (quality management system) are considered. The use of digital twins in the quality management system allows monitoring inconsistencies in the technological component of production and quickly eliminating them, and also offers solutions to the identified problem. Companies are now finding a competitive advantage in digital technologies, especially digital twins, whose economic benefits are undeniable. The quality management system of enterprises with high-tech industries is more and more moving into the analysis of big data and in interaction with the digital environment. Thus, it is so important to pay attention to technologies directly related to the analysis of the quality of the product and the processes of its creation. As a result of the study, a clear connection between advanced information technologies and the development of the quality management system of enterprises was revealed.

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Yamasaki, Fuminori. „The Digital Twin Technology Utilizing Inspection Robots“. Journal of the Robotics Society of Japan 38, Nr. 7 (2020): 600–603. http://dx.doi.org/10.7210/jrsj.38.600.

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Bezborodova, O. E., O. N. Bodin, A. I. Gerasimov, M. N. Kramm, R. F. Rahmatullov und A. G. Ubiennykh. „«Digital Twin» technology in medical information systems“. Journal of Physics: Conference Series 1515 (April 2020): 052022. http://dx.doi.org/10.1088/1742-6596/1515/5/052022.

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Dissertationen zum Thema "Digital Twin Technology"

Tabbah, Alyaá. „Evaluating digital twin data exchange between a virtual and physical environment regarding lighting quantity“. Thesis, Jönköping University, JTH, Byggnadsteknik och belysningsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53737.

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Building Information Management and Digital Twin technology with help of Smart lights can optimizethe built environment impacting our health and well-being, by providing the right amount of light at theright time of day. Lighting simulation is challenging, due to the strict requirements to represent reality. Digitaltwin technology will provide a more dynamic two-way feed-back between the physical and the virtual environmentto optimize the lighting environment giving real-time sensor data. The main problem that currently occurswhile evaluating a lighting design made in photorealistic computer visualization is using the appropriate formof their model presentation. However, validation of light simulations has been done multiple times but not manystudies are based on DT-driven light environment evaluation in which not only the realistic representation butalso the exchange of information plays a crucial role. Therefore, the aim is to develop a strategy for demonstratingthe data exchange between a physical and real environment, for a scenario in which an optimal interactionbetween daylight and electric light derives an optimized realization of a given light demand curve. Basedon a quantitative experiment, validation of a Digital Twin was done between a virtual and a physical twin onan existing room using the light simulation tool DIALux evo. Data exchange was optimized for three levels ofgeometrical complexity. The light environment was optimized for interaction between the Digital and RealTwin. Counter to expectations, the results showed that the coarse model is more accurate representation of thephysical counterpart and generates faster data exchange. Defining DT usage purpose reduces time and effortdone on the process of creation. Knowing what data to exchange and how often avoid developers any limitationsor delaying in the process. Future studies can investigate how optimization of data exchange and light environmentcan be achieved with programming and parametric generative design.

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Rajendran, Ajith, und Gautham Asokan. „Real Time Monitoring of Machining Process and Data Gathering for Digital Twin Optimization“. Thesis, KTH, Industriell produktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301594.

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In the development stages of a Digital twin of production assets, especially machine tools, real time process monitoring and data gathering proves to be vital. Having a monitoring system that monitors and updates the operators or managers in real time, helps improve productivity in terms of reducing downtime through predictive/preventive analytics and by incorporating in process quality assessment capabilities. When it comes to Real time monitoring of machine tools andprocesses, sensor technologies have proven to be the most effective and widely researched. Years of research and development have paved the way for many smart sensor technologies that come both in built with the machine tools as well as external applications. However, these technologies prove to be expensive and complicated to implement especially for Small and Medium Enterprises. This thesis focuses on evaluating and testing a simple, cost-efficient monitoring system using inexpensive sensor technologies that would help optimize an existing Digital twin setup for machine tools for Small and Medium Enterprises. Experiments with a 5 axis CNC machine tool using different tools and varying operating parameters, materials were performed,and the relevant sensor data were collected, mapped, analysed for accuracy and benchmarking. The thesis also evaluates the integration of this data with the information already collected from other sources, improve existing data reliability, and provides guidelines on this could be transformed usefully to create more value to SME’s.

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Huang, Chengxue, und Hampus Wranér. „Lifecycle management and smart manufacturing: Modelling and implementation to utilize the digital twin“. Thesis, KTH, Industriell produktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232369.

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Smart manufacturing – smart factories creating smart products – is a topic which has arisen in the academic as well as business community. This thesis covers smart manufacturing in the context of lifecycle management. The thesis investigated how the standard Product Life Cycle Support (PLCS) could be used to support smart manufacturing and mainly how to develop the underlying system and information infrastructure. Standards, reports and specifications for smart manufacturing were investigated. Several information models were created from these publications which could be used for implementing a proposed solution for the infrastructure.The implementation concerned a use case in the ongoing research project DigIn, and used the developed models to implement a proposed solution in the product lifecycle management software ShareAspace. This was done in order to evaluate how to use the functionality of PLCS and ShareAspace to utilize the solution to support smart manufacturing and update the digital twin. In parallel to this thesis, a sub-project part of the DigIn project was conducted which connected the database to other software in the system as well as to the factory shop floor. The solution used the plant service bus Kafka and REST APIs in order to establish the connection. The functionality of the system regarding the specified required functionality in the publications was then investigated.The solution was found to meet most of the requirements of the publications regarding, among others, lifecycle management, service oriented architecture, non-hierarchical structures and communication capabilities.
Smart tillverkning – smarta fabriker som skapar smarta produkter – är ett ämne som inom det akademiska och affärsmässiga området förekommer alltmer frekvent. Denna uppsats behandlar smart tillverkning i kontexten av Product Life Cycle Support (PLCS). Uppsatsen undersökte hur PLCS kunde utnyttjas för att möjliggöra smart tillverkning, med huvudsakligt fokus på möjliggörandet av den bakomliggande system- och informationsinfrastrukturen för smart tillverkning. Standarder, rapporter och specifikationer för smart tillverkning undersöktes. Flertalet informationsmodeller skapades utifrån dessa publikationer vilka kunde användas för att implementera ett förslag för infrastrukturen.Implementationen hade sin bas i det pågående forskningsprojektet DigIn, och använde de utvecklade modellerna för att implementera en föreslagen lösning i produktlivscykel-mjukvaran ShareAspace. Detta gjordes för att utvärdera hur funktionaliteten i ShareAspace och PLCS skulle kunna användas för att stödja smart tillverkning och uppdatera den digitala tvillingen. Parallellt med denna implementation genomfördes i DigIn ett projekt vilka kopplade samman databasen med annan mjukvara i systemet samt fabriksgolvet. Lösningen använde en Plant Service Bus (Kafka) och REST APIer för att koppla samman dessa. Funktionaliteten av systemet rörande specificerade krav som återfanns i publikationerna undersöktes sedan.Lösningen fanns möta de flesta av de krav som lades fram i de undersökta publikationerna rörande, bland annat, livscykelshantering, tjänsteorienterad arkitektur, icke-hierarkiska strukturer samt kommunikationsmöjligheter.

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Andersson, Ebba, und Kajsa Eckerwall. „Enabling Successful Collaboration on Digital Platforms in the Manufacturing Industry : A Study of Digital Twins“. Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-74523.

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Purpose – The purpose of this study is to enhance the understanding of how to successfully collaborate on digital platforms in the manufacturing industry by developing a contingency framework. To fulfill this purpose, the following research questions were derived: RQ1: Which challenges arise when collaborating on digital platforms in the manufacturing industry? and RQ2: How can collaboration challenges on digital platforms in the manufacturing industry be managed? Method – The study was conducted as an explorative, inductive single case study of a digital platform. More specifically, the study examined the development process of a digital twin platform created by a large high-technological company and its collaborative actors. In total, 21 interviews were conducted at eight different companies. The respondents all had experience of digital twin platforms, where some were working with digital twins sporadically and others on a daily basis. The data were analyzed through a thematic analysis. Findings – The analysis reveals that actors on digital platforms can face five types of challenges that hinder a successful collaboration: disadvantages of dependency, uncertainty regarding data management, varying customer needs, insufficient work methods, and unsuitable payment models. The analysis also reveals four strategies that can be used to address the challenges: transparency strategy, incentive model strategy, servitization strategy, and control strategy. Moreover, these findings are summarized in a contingency framework that explains which types of challenges that can be addressed with which strategies based on the specific prerequisites of each collaboration. Theoretical and practical implications – The study extends the digital platform literature by providing empirical evidence for several collaboration challenges among the actors on a digital platform, which has previously bee not been studied. Additionally, the study provides evidence of how these challenges can be addressed. Our framework helps manufacturing companies to successfully adopt digital platforms by providing managers with the tools to handle the required collaboration. Limitations and further research – The study is limited by a single case study of a specific digital platform. Thus, to extend the findings, further research that examines other contexts are recommended. Moreover, the establishment of the studied platform is currently in an early phase which limits the study to hypothetical challenges and management methods. To validate the findings, further research that examines a fully developed and implemented platform is recommended.

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Noora, Jay Maryam. „Defining infrastructure requirements for the creation of Digital Twins“. Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-51051.

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Along with the evolution of the new technologies such as industrial internet of things (IIoT), big data, cloud computing, artificial intelligence (AI), etc., the amalgamation between the cyber and physical worlds in the industrial field has become necessary to realize and achieve the smart factory and increase its productivity. The emergence of the Digital Twin (DT) concept as a technology that ties the physical and digital worlds has gained significant attention around the world during the last years. However, this concept is relatively new; the literature related to this concept is limited, and its application is still under development and requires further participation from both the industry and academia. This thesis project presented the main requirements and the steps for building a DT. Three research questions have been formulated and answered separately to fulfill the objective of this research study. The answer to the first two research questions was mainly based on surveying the scientific literature to explore this concept's background, main infrastructure, related technologies, its applications in the manufacturing domain, open issues, and some opportunities and challenges that hinder its implementation. Further, the answer to the last research question is represented in proposing a general methodology with some detailed steps for DT's building process and validating this methodology with an existing case study to show it works in practice. Further, several aspects needed for future work have also been addressed.

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Kor, Mergen. „Integration of Digital Twin and Deep Learning for facilitating Smart Planning and Construction: An Exploratory Analysis“. Thesis, Jönköping University, JTH, Byggnadsteknik och belysningsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-53385.

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The Architecture, Engineering, and Construction (AEC) industry is known to be overwhelmed with resource planning, risk management, and logistic challenges, resulting in design defects, project delivery delays, cost overruns, and contractual disputes. These challenges have instigated research in the application of advanced machine learning algorithms such as Deep learning (DL) to help with diagnostic and prescriptive analysis of causes and preventive measures. Construction 4.0 develops through continuous innovations towards digitalization and intelligence, in order to realize a considerable boost in automation, productivity, and reliability. The Digital Twins, as the next level of planning and process control and automation towards Construction 4.0, will incorporate cognitive features that enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making. However, there is still a lack of awareness regarding the real impact of DT integration, DL, and IoT, all connected to self-learning hybrid models with proactive cognitive capabilities for smart planning and construction. This study investigates the potential integration of DT and DL to facilitate smart planning and construction through an explorative analysis to identify and close this gap. Data were collected from global industry experts in a mixed approach with interviews, focus groups, and a survey focusing on the applicability and interoperability of DL integrated DT with decision-support capabilities for process optimization. Based on the results of quantitative and qualitative analyses, a conceptual model of the framework has been developed. The evaluations support that the DL integrated DT model will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making in smart planning and construction.
Pre-study for SPARK-SBE potential project

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BLOMKVIST, YLVA, und LOENBOM LEO ULLEMAR. „Improving supply chain visibility within logistics by implementing a Digital Twin : A case study at Scania Logistics“. Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279054.

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As organisations adapt to the rigorous demands set by global markets, the supply chains that constitute their logistics networks become increasingly complex. This often has a detrimental effect on the supply chain visibility within the organisation, which may in turn have a negative impact on the core business of the organisation. This paper aims to determine how organisations can benefit in terms of improving their logistical supply chain visibility by implementing a Digital Twin — an all-encompassing virtual representation of the physical assets that constitute the logistics system. Furthermore, challenges related to implementation and the necessary steps to overcome these challenges were examined. The results of the study are that Digital Twins may prove beneficial to organisations in terms of improving metrics of analytics, diagnostics, predictions and descriptions of physical assets. However, these benefits come with notable challenges — managing implementation and maintenance costs, ensuring proper information modelling, adopting new technology and leading the organisation through the changes that an implementation would entail. In conclusion, a Digital Twin is a powerful tool suitable for organisations where the benefits outweigh the challenges of the initial implementation. Therefore, careful consideration must be taken to ensure that the investment is worthwhile. Further research is required to determine the most efficient way of introducing a Digital Twin to a logistical supply chain.
I takt med att organisationer anpassar sig till de hårda krav som ställs av den globala marknaden ökar också komplexiteten i deras logistiknätverk. Detta har ofta en negativ effekt på synligheten inom logistikkedjan i organisationen, vilken i sin tur kan ha en negativ påverkan på organisationens kärnverksamhet. Målet med denna studie är att utröna de fördelar som organisationer kan uppnå vad gäller att förbättra synligheten inom deras logistikkedjor genom att implementera en Digital Tvilling — en allomfattande virtuell representation av de fysiska tillgångar som utgör logistikkedjan. Resultaten av studien är att Digitala Tvillingar kan vara gynnsamma för organisationer när det gäller att förbättra analys, diagnostik, prognoser och beskrivningar av fysiska tillgångar. Implementationen medför dock utmaningar — hantering av implementations- och driftskostnader, utformning av informationsmodellering, anammandet av ny teknik och ledarskap genom förändringsarbetet som en implementering skulle innebära. Sammanfattningsvis är en Digital Tvilling ett verktyg som lämpar sig för organisationer där fördelarna överväger de utmaningar som tillkommer med implementationen. Därmed bör beslutet om en eventuell implementation endast ske efter noggrant övervägande. Vidare forskning behöver genomföras för att utröna den mest effektiva metoden för att introducera en Digital Tvilling till en logistikkedja.

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Kornecki, Martin Lukas [Verfasser], Jochen [Akademischer Betreuer] Strube und Udo [Akademischer Betreuer] Rau. „Methoden zur Integration von Upstream und Downstream Processing für Biologics hinsichtlich Prozessentwicklung, Digital Twin und Process Analytical Technology / Martin Lukas Kornecki ; Jochen Strube, Udo Rau“. Clausthal-Zellerfeld : Technische Universität Clausthal, 2020. http://d-nb.info/1231362537/34.

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Ruderer, Marcus, und Signe Stéen. „Digitala Tvillingar : Verklighet eller hype?“ Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279724.

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Digitala tvillingar har på de senaste åren blivit ett väldigt aktuellt och omtalat begrepp. I det här examensarbetet undersöks det om termen enbart är en hype eller om det faktiskt är verktyget för att utveckla olika branscher till något bättre. Projektet fokuserar främst på produktions- och utvecklingsindustrin, men även inom exempelvis stadsplanering och motorsport förklaras det vad digitala tvillingar används till. En viktig del i projektet är även Industri 4.0 och Sakernas Internet. Syftet (och resultatet) för det utförda examensarbetet är att ta reda på vad företag anser gynnsamt, såväl som missgynnsamt med digitala tvillingar, samt fastställa vilka barriärer det finns hos ett företag för att börja använda sig av digitala tvillingar. Syftet är även att utforska hur digitala tvillingar införs i ett företags produktutvecklingsprocess, samt vilken roll en fysisk provning får hos ett företag som introducerar digitala tvillingar. I projektets syfte ingår också att ta reda på mer om digitala tvillingar ur ett utvecklingsperspektiv, för att utreda hur kapaciteten förefaller hos en produkt som är testad och utvecklad i kombination med digital och verklig miljö. Vad finns det för data att utläsa, och i vilka fall finns det potential för en digital tvilling? För att nå önskade resultat med projektet har en tablettmaskin skapats i CAD. Med hjälp av den tredimensionella modellen visas det hur en digital tvilling kan användas för produktionsanläggningar (specifikt process- och tillverkningsindustri) genom att montera sensorer på den tredimensionella modellen, som även ska monteras identiskt på en fysisk motsvarighet. Under projektets genomförande undersöks även Gartners hypekurva och därmed vad som är hype och inte hype. I slutet av rapporten diskuteras bland annat vad som är möjligt att simulera med digitala tvillingar och vad som inte är det. Slutsatsen gällande om en digital tvilling är en hype eller inte, resulterar i att digitala tvillingar är ett verktyg som blir vad det skapas till. Anses en digital tvilling vara en hype, ja då kanske det egentligen är själva förväntningarna som är överskattade, och inte den digitala tvillingen i sig.
Digital twins have in recent years become a very current and discussed concept. This thesis examines whether the term is merely a hype or whether it is the tool for developing different industries for something better. The project focuses mainly on the manufacturing and development industry, but also what digital twins are used for in e.g. urban planning and motorsport. An important part of the project is also Industry 4.0 and the Internet of Things (IoT). The purpose (and result) of this Bachelor thesis is to find out what companies consider favourable, as well as unfavourable with digital twins, and to determine what barriers a company encounters to start using digital twins. The purpose is also to explore how digital twins are introduced into a company's product development process, as well as which role a physical test at a company that introduces digital twins has. The purpose of the project also includes finding out more about digital twins from a development perspective, to investigate how the capacity of a product tested and developed in combination with digital and real environment appears. What kind of data is there to read, and in what cases is there a potential for a digital twin? To achieve the desired results, a tablet machine has been created in CAD. The threedimensional model shows how a digital twin can be used for production facilities (specific process- and manufacturing industry) by mounting sensors on the three-dimensional model, which should also be mounted equally on a physical counterpart. During the project's implementation, Gartner's hype curve is also examined and thus what is hype and not hype. At the end of the report there is a discussion including e.g. what is possible to simulate with digital twins and what is not. The conclusion regarding whether a digital twin is a hype or not, results in digital twins being a tool that becomes what it is created for. Is a digital twin considered a hype, well then maybe it is actually the expectations that are overestimated, and not the digital twin itself.

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BURKHARDT, ELLEN. „Optimization and investment decisions of electrical motors’ production line using discrete event simulation“. Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280294.

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More dynamic markets, shorter product life cycles and comprehensive variant management are challenges that dominate today's market. These maxims apply to the automotive sector, which is currently highly exposed to trade wars, changing mobility patterns and the emergence of new technologies and competitors. To meet these challenges, this thesis presents the creation of a digital twin of an existing production line of electric motors using discrete event simulation. Based on a detailed literature research, a step-by-step establishment of the simulation model of the production line using the software Plant Simulation is presented and argued. Finally, different experiments are carried out with the created model to show how a production line can be examined and optimized by means ofsimulation using different parameters. Within the scope of the different experiments regarding the number of workpiece carriers, number of operators as well as buffer sizes, the line was examined concerning the increase of the output. Furthermore, the simulation model was used to make decisions for future investments in additional XXX machines. Four different scenarios were examined and optimized. By examining the different parameters, optimization potentials of XXX% in the first scenario and up to XXX% in the fourth scenario were achieved. Finally, it was proven that the developed simulation model can be used as a tool for optimizing an existing production line and can generate useful investment information. Beyond that, the development of the simulation model can be employed to investigate further business questions at hand for the specific production line in question.
Mer dynamiska marknader, kortare produktlivscykler och omfattande varianthantering är utmaningar som dominerar dagens marknad. Dessa maximer gäller bilindustrin, som för närvarande är mycket utsatt för handelskrig, förändrade rörlighetsmönster och framväxten av ny teknik och nya konkurrenter. För att möta dessa utmaningar innebär denna avhandling skapandet av en digital tvilling av en befintlig produktionslinje av elmotorer med diskret händelsesimulering. Baserat på en detaljerad litteraturforskning presenteras och argumenteras en steg-för-steg-etablering av simuleringsmodellen för produktionslinjen med hjälp av programvaran Plant Simulation. Slutligen utförs olika experiment med den skapade modellen för att visa hur en produktionslinje kan undersökas och optimeras med hjälp av simulering med hjälp av olika parametrar. Inom ramen för de olika experimenten när det gäller antalet arbetsstyckesbärare, antalet operatörer samt buffertstorlekar undersöktes linjen om ökningen av produktionen. Dessutom användes simuleringsmodellen för att fatta beslut för framtida investeringar i ytterligare hårnålsmaskiner. Fyra olika scenarier undersöktes och optimerades. Genom att undersöka de olika parametrarna uppnåddes optimeringspotentialer på XXX % i det första scenariot och upp till XXX % i det fjärde scenariot. Slutligen bevisades det att den utvecklade simuleringsmodellen kan användas som ett verktyg för att optimera en befintlig produktionslinje och kan generera användbar investeringsinformation. Utöver detta kan utvecklingen av simuleringsmodellen användas för att undersöka ytterligare affärsfrågor till hands för den specifika produktionslinjen i fråga.

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Bücher zum Thema "Digital Twin Technology"

Chaudhary, Gopal, Manju Khari und Mohamed Elhoseny. Digital Twin Technology. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868.

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Buchteile zum Thema "Digital Twin Technology"

Arora, J., und M. Tushir. „Digital Twin“. In Digital Twin Technology, 23–45. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-2.

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Jain, Vanita, N. Luthra und D. Saini. „Digital Twin Technology“. In Digital Twin Technology, 1–21. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-1.

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Himanshu. „Nessus“. In Digital Twin Technology, 205–18. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-10.

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Gupta, Meenu, Rakesh Kumar und Divya Singh. „Crop Diseases Detection and Prevention Using AI and Machine Learning Techniques“. In Digital Twin Technology, 61–82. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-4.

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Niroumand, Hamed, Charles J. Kibert, Somayeh Asadi, Fatemeh Mahdavi und Hadi Arabi. „Wind Catchers as Earth Building“. In Digital Twin Technology, 105–33. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-6.

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Donkal, Gita, und Anjali Donkal. „Digital Twin and the Detection and Location of DoS Attacks to Secure Cyber-Physical UAS“. In Digital Twin Technology, 135–63. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-7.

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Jayanti, Jagannath, Madhavendra Singh und Vibhuti Jain. „Case Studies Related to Depression Detection Using Deep Learning Techniques“. In Digital Twin Technology, 219–35. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-11.

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Gupta, Meenu, M. Kumari und C. Ved. „Digital Twin in Agriculture Sector“. In Digital Twin Technology, 47–60. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-3.

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Gupta, Meenu, Rakesh Kumar und Sapna Dewari. „Digital Twin Techniques in Recognition of Human Action Using the Fusion of Convolutional Neural Network“. In Digital Twin Technology, 165–86. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-8.

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Jain, Vanita, Akanshu Raj, Abhishek Tanwar und Mridul Khurana. „eVote – A Decentralized Voting Platform“. In Digital Twin Technology, 187–204. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003132868-9.

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Konferenzberichte zum Thema "Digital Twin Technology"

Hämäläinen, Mervi. „Smart city dvelopment with digital twin technology“. In Enabling Technology for a Sustainable Society. University of Maribor Press, 2020. http://dx.doi.org/10.18690/978-961-286-362-3.20.

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Growing urban areas are major consumers of natural resources, energy and raw materials. Understanding cities´ urban metabolism is salient when developing sustainable and resilient cities. This paper addresses concepts of smart city and digital twin technology as means to foster more sustainable urban development. Smart city has globally been well adopted concept in urban development. With smart city development cities aim to optimize overall performance of the city, its infrastructures, processes and services, but also to improve socio-economic wellbeing. Dynamic digital twins are constituted to form real-time connectivity between virtual and physical objects. Digital twin combines virtual objects to its physical counterparts. This conceptual paper provides additionally examples from dynamic digital twin platforms and digital twin of Helsinki, Finland.

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Erol, Tolga, Arif Furkan Mendi und Dilara Dogan. „Digital Transformation Revolution with Digital Twin Technology“. In 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). IEEE, 2020. http://dx.doi.org/10.1109/ismsit50672.2020.9254288.

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Goodheart, Kevin, Peter Mas, Maged Ismail, Umberto Badiali und Wim Hendicx. „Predictive Maintenance Using the Executable Digital Twin xDT“. In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/30980-ms.

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Abstract Through the introduction of programmable logic controller (PLCs), Dynamic Process & Controls modeling, integrating with Multiphysics Mechatronics & 3D equipment simulation modeling, companies can work in the online real-time environment. This modeling of equipment or processes builds the foundation for digital transformation of subsea, topside, onshore and plant environments. In the design and operation of field equipment, the physics based Digital Twin is getting more and more traction to develop virtually the equipment because of recent prediction accuracy improvement and faster calculation times. Such digital twins allow to find the optimal operating conditions and predictive maintenance schedules for operation. In this timeslot we will explain, based on few industrial examples, a new set of capabilities that allow companies to get the maximum out of digital twins to be able to use them on their equipment. By applying a structured process using Digital Twins to be able to convert the existing knowledge & data at Companies into solution to be more predictive on their equipment. This will deliver substantial return on investment (ROI) for the Oil and Gas Industry. An AI based methodology to perform Model Order Reduction on the digital twin to be able to get real time response in connection to online unit information An AI based methodology to convert the reduced model into a virtual sensor for online quality predictions or predictive maintenance scheduling as well as to use it for creating an optimal controller of the unit based on the product requirements Fast edge computing hardware that can collect data from sensors and, in real time, run the Executable Digital Twin (xDT) and suggest corrective action to the operator or run in closed loop control

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Matsumoto, Shunsaku, Vivek Jaiswal, Tadashi Sugimura, Shintaro Honjo und Piotr Szalewski. „Mooring Integrity Management through Digital Twin and Standardized Inspection Data“. In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/31036-ms.

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Abstract This paper presents a concept of a mooring digital twin frameworkand a standardized inspection datatemplate to enable digital twin. The mooring digital twin framework supports real-time and/or on-demand decision making in mooring integrity management, which minimizes the failure risk while reducing operation and maintenance cost by efficient inspection, monitoring, repair, and strengthening. An industry survey conducted through the DeepStar project 18403 identified a standard template for recording inspection data as a high priority item to enable application of the digital twins for integrity management. Further, mooring chain was selected as a critical mooring component for which a standard inspection template was needed. The characteristics of damage/performance prediction with the proposed mooring digital twin framework are (i) to utilize surrogates and/or reduced-order models trained by high-fidelity physics simulation models, (ii) to combine all available lifecycle data about the mooring system, (iii) to evaluate current and future asset conditions in a systematic way based on the concept of uncertainty quantification (UQ). The general and mooring-specific digital twin development workflows are described with the identified essential data, physics models, and several UQ methodologies such as surrogate modeling, local and global sensitivity analyses, Bayesian prediction etc. Also, the proposed digital twin system architecture is summarized to illustrate the dataflow in digital twin development andutilization. The prototype of mooring digital twin dashboard, web-based risk visualization and advisory system, is developed to demonstrate the capability to visualize the system health diagnosis and prognosis and suggest possible measures/solutions for the high-risk components as a digital twin's insight.

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Li, Pengzhong, Hanchen Zhu und Liang Luo. „Digital Twin Technology in Intelligent Manufacturing“. In 2020 2nd International Conference on Artificial Intelligence and Advanced Manufacture (AIAM). IEEE, 2020. http://dx.doi.org/10.1109/aiam50918.2020.00046.

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Halenar, Igor, Martin Juhas, Bohuslava Juhasova und Dmitrii Borkin. „Virtualization of Production Using Digital Twin Technology“. In 2019 20th International Carpathian Control Conference (ICCC). IEEE, 2019. http://dx.doi.org/10.1109/carpathiancc.2019.8765940.

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Wu, Jiaju, Yonghui Yang, XUN Cheng, Hongfu Zuo und Zheng Cheng. „The Development of Digital Twin Technology Review“. In 2020 Chinese Automation Congress (CAC). IEEE, 2020. http://dx.doi.org/10.1109/cac51589.2020.9327756.

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Moller, Dietmar P. F., Hamid Vakilzadian und Weyan Hou. „Intelligent Manufacturing with Digital Twin“. In 2021 IEEE International Conference on Electro Information Technology (EIT). IEEE, 2021. http://dx.doi.org/10.1109/eit51626.2021.9491874.

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Podskarbi, Mat, und David J. Knezevic. „Digital Twin for Operations - Present Applications and Future Digital Thread“. In Offshore Technology Conference. Offshore Technology Conference, 2020. http://dx.doi.org/10.4043/30553-ms.

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Alves, Rafael Gomes, Gilberto Souza, Rodrigo Filev Maia, Anh Lan Ho Tran, Carlos Kamienski, Juha-Pekka Soininen, Plinio Thomaz Aquino und Fabio Lima. „A digital twin for smart farming“. In 2019 IEEE Global Humanitarian Technology Conference (GHTC). IEEE, 2019. http://dx.doi.org/10.1109/ghtc46095.2019.9033075.

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