IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v52y2022i4p390-393.html
   My bibliography  Save this article

Practice Summary: Multilaser Load Balancing in Additive Manufacturing

Author

Listed:
  • Nitish Umang

    (GE Global Research, Niskayuna, New York 12309)

  • Srinivas Bollapragada

    (GE Global Research, Niskayuna, New York 12309)

  • Kai Hertel

    (GE Additive, Concept Laser GmbH, 96215 Lichtenfels, Germany)

Abstract

Additive manufacturing is a fast-growing printing technology that uses design data to build parts in controlled three-dimensional process space. In a particular type of additive manufacturing called powder-based melting, multiple laser systems work in parallel to build parts. We developed an optimization algorithm to balance the load between the lasers to increase machine throughput and minimize build time while ensuring that lasers are not occluded by the smoke generated by other lasers. We implemented, tested, and delivered the algorithm to the GE Concept Laser software team. The algorithm is scheduled to be integrated into the GE Concept Laser M-line System, a state-of-the-art additive manufacturing printer sold by GE.

Suggested Citation

  • Nitish Umang & Srinivas Bollapragada & Kai Hertel, 2022. "Practice Summary: Multilaser Load Balancing in Additive Manufacturing," Interfaces, INFORMS, vol. 52(4), pages 390-393, July.
  • Handle: RePEc:inm:orinte:v:52:y:2022:i:4:p:390-393
    DOI: 10.1287/inte.2022.1118
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2022.1118
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2022.1118?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
    ---><---

    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:inm:orinte:v:52:y:2022:i:4:p:390-393. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.