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    Twin-Control

    A Digital Twin Approach to Improve Machine Tools Lifecycle

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    Contributor(s)
    Armendia, Mikel (editor)
    Ghassempouri, Mani (editor)
    Ozturk, Erdem (editor)
    Peysson, Flavien (editor)
    Language
    English
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    Abstract
    This open access book summarizes the results of the European research project “Twin-model based virtual manufacturing for machine tool-process simulation and control” (Twin-Control). The first part reviews the applications of ICTs in machine tools and manufacturing, from a scientific and industrial point of view, and introduces the Twin-Control approach, while Part 2 discusses the development of a digital twin of machine tools. The third part addresses the monitoring and data management infrastructure of machines and manufacturing processes and numerous applications of energy monitoring. Part 4 then highlights various features developed in the project by combining the developments covered in Parts 3 and 4 to control the manufacturing processes applying the so-called CPSs. Lastly, Part 5 presents a complete validation of Twin-Control features in two key industrial sectors: aerospace and automotive. The book offers a representative overview of the latest trends in the manufacturing industry, with a focus on machine tools.
    URI
    http://library.oapen.org/handle/20.500.12657/22911
    Keywords
    Engineering; Manufactures; Vibration; Dynamical systems; Dynamics; Control engineering; Machinery
    DOI
    10.1007/978-3-030-02203-7
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2019
    Classification
    Engines and power transmission
    Materials science
    Production and industrial engineering
    Automatic control engineering
    Pages
    296
    Rights
    https://creativecommons.org/licenses/by/4.0
    • Imported or submitted locally

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    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.

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