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Solving a multi-objective simulation model using a hybrid response surface method and lexicographical goal programming approach—a case study on integrated circuit ink-marking machines

Author

Listed:
  • T Yang

    (National Cheng Kung University)

  • L Tseng

    (National Cheng Kung University)

Abstract

In an integrated circuit (IC) packaging plant, the ink-marking machine has a significantly higher throughput than the other processing machines. When periodic demand surges result in backlog orders or in lost customers, there is a need to increase system throughput. To resolve this problem, the purchase of a new machine often results in excess capacity in addition to added operation and acquisition costs. Therefore, the productivity improvement effort has priority over the machine purchase decision. This paper seeks to optimize both throughput and cycle time performance for IC ink-marking machines. While throughput increase is the primary objective, there is an acceptable cycle time limit for a feasible solution. It is a multi-objective problem. The proposed solution methodology constructed a simulation metamodel for the ink-marking operation by using a fractional factorial experimental design and regression analysis. It is then solved by a hybrid response surface method and lexicographical goal programming approach. Solution results illustrated a successful application.

Suggested Citation

  • T Yang & L Tseng, 2002. "Solving a multi-objective simulation model using a hybrid response surface method and lexicographical goal programming approach—a case study on integrated circuit ink-marking machines," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(2), pages 211-221, February.
    • Handle: RePEc:pal:jorsoc:v:53:y:2002:i:2:d:10.1057_palgrave.jors.2601284
    DOI: 10.1057/palgrave.jors.2601284
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    Citations

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    Cited by:

    1. Yang, Taho & Fu, Hsin-Pin & Yang, Kuang-Yi, 2007. "An evolutionary-simulation approach for the optimization of multi-constant work-in-process strategy--A case study," International Journal of Production Economics, Elsevier, vol. 107(1), pages 104-114, May.
    2. Yang, Taho & Chou, Pohung, 2005. "Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(1), pages 9-21.
    3. Noguera, Jose H. & Watson, Edward F., 2006. "Response surface analysis of a multi-product batch processing facility using a simulation metamodel," International Journal of Production Economics, Elsevier, vol. 102(2), pages 333-343, August.

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