• DocumentCode
    3746896
  • Title

    Simulation studies on model selection in pm planning optimization

  • Author

    Minho Lee;James R. Morrison;Adar A. Kalir

  • Author_Institution
    Department of Industrial and Systems Engineering, KAIST, 335 Gwahangno Yuseong-gu, Daejeon, 305-701, REPUBLIC of SOUTH KOREA
  • fYear
    2015
  • Firstpage
    2929
  • Lastpage
    2940
  • Abstract
    In semiconductor manufacturing, preventive maintenance (PM) is complicated and essential. Since tool down time contributes significantly to manufacturing flow variability and thus mean cycle time, effective PM planning is important. Here we extend existing PM planning methods to allow for four categories of PM models. We study the quality of these PM models and the resulting optimized PM plans via simulation. We observe that the approximate mean cycle time formulae for these models are generally of good accuracy. Our studies show that good PM plans suggested from the use of these approximate formulae remain good plans in the true system. Finally, we study the implications of using optimized PM plans generated from one type of model in another type of model. The results suggest that good PM plans are relatively insensitive to which of the four PM models are selected.
  • Keywords
    Optimization
  • Publisher
    ieee
  • Conference_Titel
    Winter Simulation Conference (WSC), 2015
  • Electronic_ISBN
    1558-4305
  • Type

    conf

  • DOI
    10.1109/WSC.2015.7408396
  • Filename
    7408396