Logo Oapen
  • Join
    • Deposit
    • For Librarians
    • For Publishers
    • For Researchers
    • Funders
    • Resources
    • OAPEN
        View Item 
        •   OAPEN Home
        • View Item
        •   OAPEN Home
        • View Item
        JavaScript is disabled for your browser. Some features of this site may not work without it.

        Chapter 4 Digital Twins in Smart Manufacturing

        Proposal review

        Thumbnail
        Download PDF Viewer
        Author(s)
        Aziz, Shahid
        JUNG, DONG WON
        Zaman, Uzair Khaleeq uz
        Aqeel, Anas Bin
        Language
        English
        Show full item record
        Abstract
        A digital twin is a digital replica of a living or non-living physical entity, such as a manufacturing process, medical device, piece of medical equipment, and even a person to gain insight into the present and future operational states of each physical twin." With the rapid advancement in manufacturing processes through sensors, the Internet of Things (IoT), modeling software, cloud computing, and cyber-physical integration, smart manufacturing is being adopted by almost all manufacturers. Digital twin promises the realization of smart manufacturing through the interaction and utilization of all these technological advances. Therefore, it is necessary to educate the industrialists and researchers involved in the manufacturing industry on the recent progress and directions of digital twin technology and services. In general, this work introduces the digital twin technology and presents case studies specifically for smart manufacturing from the perspective of industry 4.0. It also presents the digital twin for smart product design, biomanufacturing, and IoT with case studies. It gives its readers a guideline for future trends and an application framework for product design using digital twins.
        Book
        Handbook of Manufacturing Systems and Design
        URI
        https://library.oapen.org/handle/20.500.12657/74697
        Keywords
        CAM, Computer-Aided Manufacturing, PLM, Product Lifecycle Management, CAPP, Computer-Aided Process Planning
        DOI
        10.1201/9781003327523-6
        ISBN
        9781003327523, 9781032353210, 9781032355719
        Publisher
        Taylor & Francis
        Publisher website
        https://taylorandfrancis.com/
        Publication date and place
        2024
        Grantor
        • Ministry of Science and ICT, South Korea
        Imprint
        CRC Press
        Classification
        Industrial chemistry and manufacturing technologies
        Production and industrial engineering
        Technical design
        Pages
        17
        Rights
        https://creativecommons.org/licenses/by-nc-nd/4.0/
        • Imported or submitted locally

        Browse

        All of OAPENSubjectsPublishersLanguagesCollections

        My Account

        LoginRegister

        Export

        Repository metadata
        Logo Oapen
        • For Librarians
        • For Publishers
        • For Researchers
        • Funders
        • Resources
        • OAPEN

        Newsletter

        • Subscribe to our newsletter
        • view our news archive

        Follow us on

        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

        OAPEN is based in the Netherlands, with its registered office in the National Library in The Hague.

        Director: Niels Stern

        Address:
        OAPEN Foundation
        Prins Willem-Alexanderhof 5
        2595 BE The Hague
        Postal address:
        OAPEN Foundation
        P.O. Box 90407
        2509 LK The Hague

        Websites:
        OAPEN Home: www.oapen.org
        OAPEN Library: library.oapen.org
        DOAB: www.doabooks.org

         

         

        Export search results

        The export option will allow you to export the current search results of the entered query to a file. Differen formats are available for download. To export the items, click on the button corresponding with the preferred download format.

        A logged-in user can export up to 15000 items. If you're not logged in, you can export no more than 500 items.

        To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

        After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.