IDEAS home Printed from https://ideas.repec.org/a/taf/tjsmxx/v18y2024i5p813-834.html
   My bibliography  Save this article

Live fitting of process data within digital twins of manufacturing to use simulation and optimisation

Author

Listed:
  • Christin Schumacher
  • Jonas Stilling
  • Jan Kriege
  • Peter Buchholz

Abstract

In production scenarios, uncertainty in production times, and scrap rates is common. Uncertainty can be described by stochastic models that need continuous updates due to changing conditions. This paper models probability distributions and estimates their parameters from real-world data on processing times and scrap rates. It uses live fitting to identify timely changes in the data sets, comparing different distributions. The fitting and live fitting approaches are applied to data from a real production system to compare the goodness of fit for different distributions and to demonstrate the reliability of the reaction to changes in the input data. Data and probability estimations are categorised, and a concept combining simulation and optimisation models is developed to optimise scheduling. The vision of the research presented in this paper is an online approach that determines quasi-optimal schedules for production systems based on current data from the system and its environment.

Suggested Citation

  • Christin Schumacher & Jonas Stilling & Jan Kriege & Peter Buchholz, 2024. "Live fitting of process data within digital twins of manufacturing to use simulation and optimisation," Journal of Simulation, Taylor & Francis Journals, vol. 18(5), pages 813-834, September.
    • Handle: RePEc:taf:tjsmxx:v:18:y:2024:i:5:p:813-834
    DOI: 10.1080/17477778.2024.2376711
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/17477778.2024.2376711
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/17477778.2024.2376711?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    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:taf:tjsmxx:v:18:y:2024:i:5:p:813-834. 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 Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjsm .

    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.