• DocumentCode
    2847367
  • Title

    Efficient scheduling method based on an assignment model for robotized cluster tools

  • Author

    Jung, Chihyun ; Lee, Tae-Eog

  • Author_Institution
    Dept. of Ind. Eng., Korea Adv. Inst. of Sci. & Technol. (KAIST), Taejon
  • fYear
    2008
  • fDate
    23-26 Aug. 2008
  • Firstpage
    79
  • Lastpage
    84
  • Abstract
    A cluster tool consists of several wafer processing modules and material handling robot(s). Cluster tools are being prevalently used for semiconductor manufacturing. The scheduling problem is complicated due to no intermediate buffer and diverse wafer flow patterns. We examine the scheduling problem when operations are repetitively performed in a cyclic order. We propose a way of modeling a Petri net for cluster tool operation. By examining the Petri net model, we develop a mixed integer programming model as a version of well-known assignment problem for determining a deadlock-free optimal schedule that maximizes the throughput rate. By using well-known efficient algorithms for assignment problems, we efficiently compute an optimal schedule for dual-armed or single-armed cluster tools, cluster tools with reentrant wafer flows and cyclic cleaning operations.
  • Keywords
    Petri nets; cleaning; industrial robots; integer programming; materials handling equipment; scheduling; semiconductor device manufacture; Petri net model; cyclic cleaning operation; deadlock-free optimal schedule; material handling robot; mixed integer programming model; reentrant wafer flow; robotized cluster tool; scheduling problem; semiconductor manufacturing; single-armed cluster tool; wafer processing module; Clustering algorithms; Job shop scheduling; Linear programming; Materials handling; Optimal scheduling; Robots; Semiconductor device manufacture; Semiconductor device modeling; System recovery; Throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    978-1-4244-2022-3
  • Electronic_ISBN
    978-1-4244-2023-0
  • Type

    conf

  • DOI
    10.1109/COASE.2008.4626441
  • Filename
    4626441