Digital Twin Driven Smart Design draws on the latest industry practice and research to establish a basis for the implementation of digital twin technology in product design. Coverage of relevant design theory and methodology is followed by detailed discussions of key enabling technologies that are supported by cutting-edge case studies of implementation. This groundbreaking book explores how digital twin technology can bring improvements to different kinds of product design process, including functional, lean and green. Drawing on the work of researchers at the forefront of this technology, this book is the ideal guide for anyone interested in digital manufacturing or computer-aided design.

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 is about the engineering of Digital Twins (DTs) of cyber-physical systems (CPSs). It goes behind the glossy image of DTs to help researchers and advanced professionals to ask and answer the fundamental questions underpinning the development of a DT. What are the foundational concepts of the DT? How do different engineering disciplines interact in creating a DT? How should the physical and digital worlds be connected, and how do the imperfections and faults inherent in both worlds affect the DT's qualities? How can we use a DT to support decisions, and how do we maintain it through life? To this end, the book is structured in five parts: "Foundations" introduces the DT concept, the potential benefits of DTs seen from a business perspective, and foundations for DT engineering. "Models and Data" presents the range of models and data that form the core assets of DTs for CPSs. It covers ways in which models can be produced and calibrated, and considers how data is derived from a CPS and communicated to its DT. Next, "Services for Digital Twins" details some of the main services that a DT provides by building on the assets of models and data, including visualisation, fault detection and diagnosis and support for decision-making. "Realising Digital Twins" then covers the realisation of DTs, including a platform allowing engineers to construct DTs from reusable components. Case studies in food production, robotics and marine engineering are presented using a systematic framework that aligns with the DT engineering concepts introduced in the earlier parts of the book. Eventually, "Advanced Topics in Digital Twins" introduces advanced topics in delivering dependable DT-enabled systems, focusing on security and privacy, the capacity for autonomy, and a range of open research topics. This book aims at researchers in DT technology and design, including advanced (master and doctoral) students, as well as engineering practitioners aiming to develop DTs. The most common techniques described in the main text will be accessible via open-source projects, including further DT examples, exercises and solutions, as well as pointers to emerging standards, frameworks and platforms. Classroom materials, exercises and solutions are available to lecturers through a dedicated Web site.

This is the second of two volumes that together provide an overview of the latest advances in the generation and application of digital twins in bioprocess design and optimization. Both processes have undergone significant changes over the past few decades, moving from data-driven approaches into the 21st-century digitalization of the bioprocess industry. Moreover, the high demand for biotechnological products calls for efficient methods during research and development, as well as during tech transfer and routine manufacturing. In this regard, one promising tool is the use of digital twins, which offer a virtual representation of the bioprocess. They reflect the mechanistics of the biological system and the interactions between process parameters, key performance indicators and product quality attributes in the form of a mathematical process model. Furthermore, digital twins allow us to use computer-aided methods to gain an improved process understanding, to test and plan novel bioprocesses, and to efficiently monitor them. This book focuses on the application of digital twins in various contexts, e.g. computer-aided experimental design, seed train prediction, and lifeline analysis. Covering fundamentals as well as applications, the two volumes offers the ideal introduction to the topic for researchers in academy and industry alike.

Digital Twin Development and Deployment in the Cloud: Developing Cloud-Friendly Dynamic Models Using Simulink®/SimscapeTM and Amazon AWS promotes a physics-based approach to the field of digital twins. Through the use of multiphysics models running in the cloud, significant improvement to the diagnostics and prognostic of systems can be attained. The book draws a clear definition of digital twins, helping business leaders clearly identify the value it brings. In addition, it outlines the key elements needed for deployment, including the hardware and software tools needed. Special attention is paid to the process of developing and deploying the multi-physics models of the digital twins. - Provides a high-level overview of digital twins and their underutilization in the field of asset management and maintenance - Proposes a streamline process to create digital twins for a wide variety of applications using MATLAB® SimscapeTM - Deploys developed digital twins on Amazon Web Services - Includes MATLAB and Simulink codes available for free download on MATLAB central - Covers popular prototyping hardwares, such as Arduino and Raspberry Pi

This book presents an internationally comprehensive perspective into the field of complex systems. It explores the challenges of and approaches to complexity from a broad range of disciplines, including big data, health care, medicine, mathematics, mechanical and systems engineering, air traffic control and finance. The book’s interdisciplinary character allows readers to identify transferable and mutually exclusive lessons learned among these disciplines and beyond. As such, it is well suited to the transfer of applications and methodologies between ostensibly incompatible disciplines. This book provides fresh perspectives on comparable issues of complexity from the top minds on systems thinking.

Digital Twin Driven Smart Manufacturing examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process.The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards intelligent, and connected manufacturing systems. This book provides an ideal entry point to this subject for readers in industry and academia, as it answers the questions: (a) What is a digital twin? (b) How to construct a digital twin? (c) How to use a digital twin to improve manufacturing efficiency? (d) What are the essential activities in the implementation of a digital twin? (e) What are the most important obstacles to overcome for the successful deployment of a digital twin? (f) What are the relations between digital twin and New Technologies? (g) How to combine digital twin with the New Technologies to achieve high efficiency and smartness in manufacturing?This book focuses on these problems as it aims to help readers make the best use of digital twin technology towards smart manufacturing. - Analyzes the differences, synergies and possibilities for integration between digital twin technology and other technologies, such as big data, service and Internet of Things - Discuss new requirements for a traditional three-dimension digital twin and proposes a methodology for a five-dimension version - Investigates new models for optimized manufacturing, prognostics and health management, and cyber-physical fusion based on the digital twin