IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i9p1029-d547815.html
   My bibliography  Save this article

Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication

Author

Listed:
  • Ying-Mei Tu

    (Department of Industrial Management, Chung Hua University, Hsinchu 300, Taiwan)

Abstract

Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

Suggested Citation

  • Ying-Mei Tu, 2021. "Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication," Mathematics, MDPI, vol. 9(9), pages 1-13, May.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:9:p:1029-:d:547815
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/9/1029/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/9/1029/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chandra Sen Mazumdar & M. Mathirajan & R. Gopinath & A.I. Sivakumar, 2008. "Tabu Search methods for scheduling a burn-in oven with non-identical job sizes and secondary resource constraints," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 3(1/2), pages 119-139.
    2. Andreas Klemmt & Gerald Weigert & Sebastian Werner, 2011. "Optimisation approaches for batch scheduling in semiconductor manufacturing," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 5(3), pages 338-359.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mario Versaci, 2022. "Preface to the Special Issue “Mathematical Modeling in Industrial Engineering and Electrical Engineering”—Special Issue Book," Mathematics, MDPI, vol. 10(21), pages 1-5, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fowler, John W. & Mönch, Lars, 2022. "A survey of scheduling with parallel batch (p-batch) processing," European Journal of Operational Research, Elsevier, vol. 298(1), pages 1-24.
    2. C Almeder & L Mönch, 2011. "Metaheuristics for scheduling jobs with incompatible families on parallel batching machines," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2083-2096, December.
    3. Hadi Mokhtari & Amir Noroozi, 2018. "An efficient chaotic based PSO for earliness/tardiness optimization in a batch processing flow shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1063-1081, June.

    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:gam:jmathe:v:9:y:2021:i:9:p:1029-:d:547815. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.