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Intelligent Process Automation: An Application in Manufacturing Industry

  • Federico A. Lievano-Martínez
  • , Javier D. Fernández-Ledesma
  • , Daniel Burgos
  • , John W. Branch-Bedoya
  • , Jovani A. Jimenez-Builes

    Research output: Contribution to scientific journalArticle in an indexed scientific journalpeer-review

    50 Scopus citations

    Abstract

    Background: The intelligent processes automation has been cataloged as one of the most potential and strategic technology solutions to develop a corporate digital transformation. Method: This paper introduces essential concepts to create Intelligent Process Automation (IPA) in industries and proposes a framework to implement IPA technologies successfully. The approach involves: firstly, assembling a good implementation setup and deeply researching the process using process mining techniques. Secondly, choosing and locating the best AI technology inside the IPA. Finally, defining an appropriate architecture of the IPA. Results: The paper illustrates an IPA use case in the manufacturing industry, where it is possible to automate the process of sending production orders to a manufacturing plant and optimize waste and plant capacity significantly. Conclusions: The research depicts the potential of intelligent process automation and its quantifiable benefits in the manufacturing process, and the contribution can be applied to different enterprises with a global context.

    Original languageEnglish
    Article number8804
    JournalSustainability (Switzerland)
    Volume14
    Issue number14
    DOIs
    StatePublished - Jul 2022

    Bibliographical note

    Publisher Copyright:
    © 2022 by the authors.

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Keywords

    • artificial intelligence
    • cognitive automation
    • intelligent process automation
    • robotic process automation

    Types Minciencias

    • Artículos de investigación con calidad A1 / Q1

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