IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-030-94617-3_28.html
   My bibliography  Save this book chapter

Economic Indicators of the Algorithm for Introducing Artificial Intelligence into the Automated Process Control System

In: Digital Transformation in Industry

Author

Listed:
  • Maksim Vlasov

    (Institute of Economics of the Ural Branch of the Russian Academy of Sciences
    Ural Federal University)

  • Anna Lapteva

    (Ural Federal University)

Abstract

The relevance of the paper is due to the digitalization of the economy and the introduction of artificial intelligence in production processes. This paper attempts to assess the effectiveness of artificial intelligence for the automation of production. Thus, the purpose of the work is to evaluate the effect of the introduction of artificial intelligence into automated process control systems. For this, an algorithm for implementing artificial intelligence was developed, i.e., procedures and their sequence were identified when implementing artificial intelligence in automated process control systems. The following procedures were considered: selection of implemented artificial intelligence functions, selection of an artificial intelligence system, selection of hardware implementation and acquisition of artificial intelligence, formation of tests for artificial intelligence training, implementation of artificial intelligence, and evaluation of results of implementing artificial intelligence. When implementing artificial intelligence, one should choose artificial intelligence based on neural networks with deep learning. The ambiguity of the cost estimate existed when selecting hardware due to the lack of data from developed artificial intelligence versions. This complicates the definition of capital expenditures. A formula for calculating costs of implementing artificial intelligence costs in automated process control systems is proposed. The introduction of artificial intelligence into an automated process control system will not provide significant savings. Such conclusions are drawn on the basis of the calculation method.

Suggested Citation

  • Maksim Vlasov & Anna Lapteva, 2022. "Economic Indicators of the Algorithm for Introducing Artificial Intelligence into the Automated Process Control System," Lecture Notes in Information Systems and Organization, in: Vikas Kumar & Jiewu Leng & Victoria Akberdina & Evgeny Kuzmin (ed.), Digital Transformation in Industry, pages 409-422, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-94617-3_28
    DOI: 10.1007/978-3-030-94617-3_28
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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:spr:lnichp:978-3-030-94617-3_28. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.