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Allocating metrology capacity to multiple heterogeneous machines

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  • Stéphane Dauzère-Pérès
  • Michael Hassoun
  • Alejandro Sendon

Abstract

The measurement of lots to check process quality is crucial but also a non-added value operation in manufacturing systems. This paper is motivated by semiconductor manufacturing, where metrology tools are expensive, thus limiting metrology capacity which must be optimally used. In a context where multiple heterogeneous machines are sharing a common metrology workshop, the problem of minimising risk while considering metrology capacity arises. An integer linear programming (ILP) model is presented, which corresponds to a multiple-choice knapsack problem. Simple rounding heuristics are proposed, whose results on randomly generated instances are compared with the optimal solutions obtained using a standard solver on the ILP. Additionally, numerical experiments on industrial data are presented and discussed.

Suggested Citation

  • Stéphane Dauzère-Pérès & Michael Hassoun & Alejandro Sendon, 2016. "Allocating metrology capacity to multiple heterogeneous machines," International Journal of Production Research, Taylor & Francis Journals, vol. 54(20), pages 6082-6091, October.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:20:p:6082-6091
    DOI: 10.1080/00207543.2016.1187775
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    Cited by:

    1. Dauzère-Pérès, Stéphane & Hassoun, Michael, 2020. "On the importance of variability when managing metrology capacity," European Journal of Operational Research, Elsevier, vol. 282(1), pages 267-276.

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