IDEAS home Printed from https://ideas.repec.org/a/alk/jcsts0/v7y2025i3id9415.html

AI-Driven Automation for Aerospace Manufacturing: Enhancing Quality Control through Integrated Systems

Author

Listed:
  • Kiran Kumar Gunakala

    (Sri Venkateswara University, India)

Abstract

Aerospace manufacturing represents one of the most demanding precision engineering environments, requiring exacting quality control measures to ensure component integrity. Traditional manual inspection processes face significant challenges, including fatigue-induced errors, inconsistency between operators, and limited defect detection capabilities, particularly for microscopic anomalies in advanced composite materials. The integration of artificial intelligence through SAP's enterprise technology stack offers a transformative solution, enabling real-time defect detection with unprecedented accuracy and consistency. This comprehensive integration architecture connects SAP AI Core's computer vision capabilities with the SAP Integration Suite and S/4HANA Manufacturing, creating an end-to-end quality assurance ecosystem. Implementation across leading aerospace manufacturers demonstrates substantial improvements in defect detection accuracy, inspection speed, and cost efficiency. Beyond immediate operational benefits, these systems contribute to enhanced aircraft safety through comprehensive digital thread capabilities and predictive quality interventions, representing a fundamental advancement in aerospace manufacturing quality assurance.

Suggested Citation

  • Kiran Kumar Gunakala, 2025. "AI-Driven Automation for Aerospace Manufacturing: Enhancing Quality Control through Integrated Systems," Journal of Computer Science and Technology Studies, Al-Kindi Center for Research and Development, vol. 7(3), pages 644-650, April.
  • Handle: RePEc:alk:jcsts0:v:7:y:2025:i:3:id:9415
    DOI: 10.32996/jcsts.2025.7.3.73
    as

    Download full text from publisher

    File URL: https://al-kindipublisher.com/index.php/jcsts/article/view/9415
    File Function: Abstract page
    Download Restriction: no

    File URL: https://al-kindipublisher.com/index.php/jcsts/article/download/9415/8066
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.32996/jcsts.2025.7.3.73?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

    ;
    ;
    ;
    ;
    ;

    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:alk:jcsts0:v:7:y:2025:i:3:id:9415. 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: Al-Kindi Center for Research and Development (email available below). General contact details of provider: https://al-kindipublisher.com/index.php/jcsts .

    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.