• DocumentCode
    3273238
  • Title

    An optimization approach for parallel machine problems with dedication constraints: Combining simulation and capacity planning

  • Author

    Klemmt, Andreas ; Weigert, Gerald

  • Author_Institution
    Electron. Packaging Lab., Tech. Univ. Dresden, Dresden, Germany
  • fYear
    2011
  • fDate
    11-14 Dec. 2011
  • Firstpage
    1981
  • Lastpage
    1993
  • Abstract
    The main idea of the presented new approach is to join a discrete event simulation (DES) and mathematical programming techniques (i.e. mixed integer programming, MIP) for optimization of complex manufacturing processes. Thereby, a DES model allows a detailed problem description. For a target oriented optimization several capacity allocation problems are solved by a MIP solver, reducing the degrees of freedom in the DES model. As an example a typical parallel machine scheduling problem arising in semiconductor industry was chosen. Different process constraints like machine dedications, setups, auxiliary resources and processing time dependences are discussed - advantages and disadvantages of simulation-based and exact scheduling approaches are drafted. The investigated optimization goals comprise the reduction of total tardiness and setups efforts as well as a balanced machine utilization. Based on real manufacturing data of a wafer test area this approach is evaluated.
  • Keywords
    capacity planning (manufacturing); discrete event simulation; manufacturing processes; mathematical programming; parallel machines; semiconductor industry; DES; capacity planning; complex manufacturing process; dedication constraints; discrete event simulation; mathematical programming; optimization; parallel machine problems; semiconductor industry; Dispatching; Job shop scheduling; Mathematical model; Optimization; Parallel machines; Resource management; Schedules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), Proceedings of the 2011 Winter
  • Conference_Location
    Phoenix, AZ
  • ISSN
    0891-7736
  • Print_ISBN
    978-1-4577-2108-3
  • Electronic_ISBN
    0891-7736
  • Type

    conf

  • DOI
    10.1109/WSC.2011.6147912
  • Filename
    6147912