IDEAS home Printed from https://ideas.repec.org/h/ito/pchaps/259765.html
   My bibliography  Save this book chapter

Applied Mathematics Tools in Digital Transformation

In: Digital Transformation - Towards New Frontiers and Business Opportunities

Author

Listed:
  • Francesco Calabro
  • Maurizio Ceseri
  • Roberto Natalini

Abstract

Digital transformation is a process that companies start with different purposes. Once an enterprise embarks on a digital transformation process it translates all its business processes (or, at least, part of them) into a digital replica. Such a digital replica, the so-called digital twin, can be described by Mathematical Science tools allowing cost reduction on industrial processes, faster time-to-market of new products and, in general, an increase of competitive advantage for the company. Digital twin is a descriptive or predictive model of a given industrial process or product that is a valuable tool for business management, both in planning--because it can give different scenario analysis--and in managing the daily operations; moreover, it permits optimization of product and process operations. We present widespread applied mathematics tools that can help this modeling process, along with some successful cases.

Suggested Citation

  • Francesco Calabro & Maurizio Ceseri & Roberto Natalini, 2022. "Applied Mathematics Tools in Digital Transformation," Chapters, in: Antonella Petrillo & Fabio De Felice & Monica Violeta Achim & Nawazish Mirza (ed.), Digital Transformation - Towards New Frontiers and Business Opportunities, IntechOpen.
    • Handle: RePEc:ito:pchaps:259765
    DOI: 10.5772/intechopen.103806
    as

    Download full text from publisher

    File URL: https://www.intechopen.com/chapters/81110
    Download Restriction: no
    File URL: https://libkey.io/10.5772/intechopen.103806?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    data mining; digital twin; modeling simulation optimization (MSO); numerical linear algebra; scientific machine learning;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ito:pchaps:259765. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Slobodan Momcilovic (email available below). General contact details of provider: http://www.intechopen.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.