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A digital twin is a digital representation of a real-world counterpart, which can receive and provide data to create value within a use case. Digital twins create value for users by enabling new and enhanced smart services. However, ambiguous definitions and terminology coupled with a lack of shared conceptual reference frameworks complicate cross-functional discussions and hinder the widespread implementation of digital twins. This thesis proposes a new definition and presents two conceptual reference frameworks to systematically depict value creation with digital twins. A design science research approach with mixed methods was used to iteratively design and evaluate these artifacts while ensuring scientific rigor, practical relevance, and usefulness. The applied methods within the five research phases include systematic literature research, interviews, workshops with academic experts, qualitative and quantitative questionnaires, workshops with practice experts, and an in-depth case study in smart waste management. The major findings of this research are (i) the proposal of a new definition of digital twins that reflects a practical understanding by focusing on value creation; (ii) a scientific conceptual reference framework focusing on completeness by distinguishing 81 elements involved in value creation with digital twins; (iii) a second, more application-oriented conceptual reference framework focusing on the interrelations of the elements essential for the value creation in practice; and (iv) an instantiation of the application-oriented framework for the use case of the in-depth case study. All artifacts are consistent in content and include the following main dimensions, which are to be considered when creating value with digital twins: data resources, internal value creation, and external value creation. These artifacts contribute to a common understanding of value creation with digital twins in research and practice. Furthermore, they enable researchers and practitioners to structure their digital twin activities and communicate them to internal and external stakeholders.
Build your first digital twin MVP and gain first-hand experience of using the technology, the challenges it presents, and its impact on your organization Key FeaturesCreate a digital twin prototype using Microsoft Azure Digital TwinExplore the digital twin approach to the design, operations, and maintenance of industrial assets and productsUnderstand key characteristics and components of a digital twin through practical use cases and business scenariosBook Description Digital twin technology enables organizations to create digital representations of physical entities such as assets, systems, and processes throughout their life cycle. It improves asset performance, utilization, and safe operations and reduces manufacturing, operational, and maintenance costs. The book begins by introducing you to the concept of digital twins and sets you on a path to develop a digital twin strategy to positively influence business outcomes in your organization. You'll understand how digital twins relate to physical assets, processes, and technology and learn about the prerequisite conditions for the right platform, scale, and use case of your digital twins. You'll then get hands-on with Microsoft's Azure Digital Twins platform for your digital twin development and deployment. The book equips you with the knowledge to evaluate enterprise and specialty platforms, including the cloud and industrial IoT required to set up your digital twin prototype. Once you've built your prototype, you'll be able to test and validate it relative to the intended purpose of the twin through pilot deployment, full deployment, and value tracking techniques. By the end of this book, you'll have developed the skills to build and deploy your digital twin prototype, or minimum viable twin, to demonstrate, assess, and monitor your asset at specific stages in the asset life cycle. What you will learnIdentify key criteria for the applicability of digital twins in your organizationExplore the RACI matrix and rapid experimentation for choosing the right tech stack for your digital twin systemEvaluate public cloud, industrial IoT, and enterprise platforms to set up your prototypeDevelop a digital twin prototype and validate it using a unit test, integration test, and functional testPerform an RoI analysis of your digital twin to determine its economic viability for the businessDiscover techniques to improve your digital twin for future enhancementsWho this book is for The digital twin book is for mid-career subject experts, including engineers and operations managers, building their first prototype (MVP) using digital twin technology. The book will help professionals responsible for mechanical, process, and reliability engineering domains. You don't have to be a developer or programmer, but beginner-level programming skills will be helpful.
This book offers state-of-the-art descriptions of intelligent service innovations in industry, supported by novel scientific approaches. It gathers findings presented at the 3rd Intelligent Services Summit, which took place in Zurich in September 2020, and chiefly focused on the design and application of Digital Twin as an enabler for business development in the field of smart services. Divided into three parts, the book addresses the challenges involved in the successful development and implementation of smart services for industry and science, ranging from data management to product design and lifecycle management. The four main aspects covered are industrial challenges, value system design (how to integrate resources into service ecosystems to create value), value creation through value proposition (how to create value for ecosystem actors), and value capture (how to create value for ecosystem businesses). Given its scope, the book offers an essential guide for practitioners and advanced students alike.
This book covers the most important subjects of digital twin in a process plant, including foundations, methods, achievements, and applications in a brownfield environment. Besides offering a variety of applications and procedural variants from research and industrial practice, this book also provides a comprehensive insight into holistic plant planning. It also discusses the challenges that currently exist in different application areas. This book would be of interest to industry professionals and researchers in industrial and manufacturing engineering.
The energy industry worldwide is facing one of the most profound changes in its history, which will be accompanied by breakthrough innovations and the exponentially evolving use of artificial intelligence in business processes. In addition to the use of artificial intelligence and AI-supported unmanned systems (on land, at sea and in the air), distributed-ledger-technologies, extended reality and 3D-print based on cyber-physical systems and the Internet of Things, as well as process mining, robotic process automation, data science and cloud computing, for example, will not only decisively shape a sustainable energy supply system in the future, but also accelerate the transformation to energy industry 4.0. At the same time, the increasingly strong networking (smart grid, smart meter, smart home, smart city) of the energy industry and its environment is associated with a growing risk potential, which must be expanded in the future as part of a high-quality cyber resilience, in particular through the use of artificial intelligence. Without the development and use of innovations and artificial intelligence in the context of increasingly digitized business processes, there is a risk that neither the energy transition can be successfully implemented nor climate change combated. In addition to the fundamentals of the classic, primarily analog energy industry, the publication addresses the possible paradigm shift that will be characterized by innovations, disruptive technologies and digital business models in the energy industry.
Increase the value of your companies by seizing the true power of digital transformation The Tesla Model S. The Uber aggregator business model. The Amazon bookstore. What do they all have in common? They're all smart. Smart products, smart business models and smart services created by data-driven tech companies that have dominated their industries and produced outsized returns for their investors. Now the high technology of digital transformation has matured to enable any traditional company to increase its competitiveness and growth profile by developing tech-facilitated business models and other intangible assets. A digitally transformed company uses data to increase its sales through innovation and invention, to increase its margins through operational efficiency and to increase its valuation multiple through the digital rerate. Founder and principle consultant of today's leading digital operating partners firm, Bruce Sinclair has been helping companies digitally transform for almost a decade, first as an independent consultant and then as an operating partner for a middle-market private equity firm. Whereas his first book, IoT Inc, is the gold standard business book for leadership in enterprises, this book applies those lessons for value creation in private equity. Digital transformation is leading to structural changes in all industries, and associated with any such changes are investment opportunities. Not just by betting on smart companies, but by buying companies and making them smart. This is your playbook to seizing the true power of digital transformation for your portfolio companies.
Over the last two decades, Digital Twins (DTs) have become the intelligent representation of future development in industrial production and daily life. Consisting of over 50 chapters by more than 100 contributors, this comprehensive handbook explains the concept, architecture, design specification and application scenarios of DTs. As a virtual model of a process, product or service to pair the virtual and physical worlds, DTs allow data analysis and system monitoring by using simulations. The fast-growing technology has been widely studied and developed in recent years. Featured with centralization, integrity and dynamics, it is cost-effective to drive innovation and performance. Many fields saw the adaptation and implementation across industrial production, healthcare, smart city, transportation and logistics. World-famous enterprises such as Siemens, Tesla, ANSYS and General Electric have built smart factories and pioneered digital production, heading towards Industry 4.0. This book aims to provide an in-depth understanding and reference of DTs to technical personnel in the field, students and scholars of related majors, and general readers interested in intelligent industrial manufacturing.
Digital agriculture is an emerging concept of modern farming that refers to managing farms using modern Engineering, Information and Communication Technologies (EICT) aiming at increasing the overall efficiency of agricultural production, improving the quantity and quality of products, and optimizing the human labor required and natural resource consumption in operations. This encyclopedia is designed to collect the summaries of knowledge on as many as subjects or aspects relevant to ECIT for digital agriculture, present such knowledge in entries, and arrange them alphabetically by articles titles. Springer Major Reference Works platform offers Live Update capability. Our reference work takes full advantage of this feature, which allows for continuous improvement or revision of published content electronically. The Editorial Board Dr. Irwin R. Donis-Gonzalez, University of California Davis, Dept. Biological and Agricultural Engineering, Davis, USA (Section: Postharvest Technologies) Prof. Paul Heinemann, Pennsylvania State University, Department Head of Agricultural and Biological Engineering, PA, USA (Section: Technologies for Crop Production) Prof. Manoj Karkee, Washington State University, Center for Precision and Automated Agricultural Systems, Washington, USA (Section: Robotics and Automation Technologies) Prof. Minzan Li, China Agricultural University, Beijing, China (Section: Precision Agricultural Technologies) Prof. Dikai Liu, University of Technology Sydney (UTS),Faculty of Engineering & Information Technologies, Broadway NSW, Australia (Section: AI, Information and Communication Technologies) Prof. Tomas Norton, University of Leuven, Dept. of Biosystems, Heverlee Leuven, Belgium (Section: Technologies for Animal and Aquatic Production) Dr. Manuela Zude-Sasse, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Precision Horticulture, Potsdam, Germany (Section: Engineering and Mechanization Technologies)
The Digital Twin book is about harnessing the power of technology, business practices, and the digital infrastructure to make revolutionary improvements for the benefit of society. Ninety experts from around the world contributed to summarize four decades of digital advances and successes, and to define the Digital Twin’s potential for the decades ahead. The book describes how Digital Twins will play a key role in specific applications and across important sectors of the global economy, making it a must-read for executives, policymakers, technical leaders, researchers, and students alike. The book consists of thirty-eight chapters that cover Digital Twin concepts, supporting technologies, practices, and specific implementation strategies for various production and service sectors. Digital Twins are about creating faster, less expensive, and error-free manufacturing, products, processes, and services. This includes engineering of systems for energy, communications, construction, transportation, and food processing. It also covers solutions for making human existence better and more enjoyable through the life sciences, smart cities, and artistic creations. The Digital Twin’s functionality addresses the entire lifecycle of products and services. Importantly, the book describes the journey required for businesses and public organizations to embrace Digital Twins as part of their tool kit. The Digital Twin is the ideal starting point for teaching and research in all application domains.
This handbook comprehensively covers the cutting-edge trends and techniques essential for the integration of nondestructive evaluation (NDE) into the changing face of the modern industrial landscape. In particular, it delves into the marriage of NDE with new techniques in e.g. data mining, cloud computing and autonomous operation, highlighting the potential for cyber-physical controlled production and discussing the myriad possible applications across many different industries. The Handbook of NDE 4.0 centers around the Internet of Things and Industry 4.0 – the next generation of industrial production encompassing all aspects of networking across all industrial areas. It discusses the adaptation of existing NDE techniques to emerging new technological areas, such as 3D printing, via the introduction of cyber systems into the inspection and maintenance processes. In addition, the handbook covers topics such as the management and processing of big data with respect to real-time monitoring of structural integrity and reliable inspection of individual components. Remote NDE to include competence not available on-site will be a potential technique to increase reliability of NDE inspections by integrating additional specialist inputs into the decision process by methods such as telepresence, thereby better leveraging the scarce resources of senior inspectors into industrial inspections at multiple sites. The handbook houses a wealth of essential information to help academics, industry professionals and entrepreneurs navigate through this burgeoning new field. The material in this handbook is presented with the intention of ultimately improving human safety through reliable inspections and dependable maintenance of critical infrastructure, while also enhancing business value through reduced downtime, affordable maintenance, and talent optimization.