Allocating metrology capacity to multiple heterogeneous machines |
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Authors: | Stéphane Dauzère-Pérès Alejandro Sendon |
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Affiliation: | 1. Department of Manufacturing Sciences and Logistics, CMP, Ecole des Mines de Saint-Etienne, CNRS UMR 6158, LIMOS, Gardanne, France.;2. Department of Accounting, Auditing and Business Analytics, BI Norwegian Business School, Oslo, Norway.;3. STMicroelectronics Rousset, ZI de Rousset, Rousset, France. |
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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. |
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Keywords: | semiconductor manufacturing metrology integer linear programming heuristics multiple-choice knapsack problem |
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