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Allocating metrology capacity to multiple heterogeneous machines

机译:将计量能力分配给多个异构机器

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摘要

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.
机译:计量批次以检查过程质量至关重要,但在制造系统中也是非附加值的操作。本文的动机是半导体制造,因为这里的计量工具很昂贵,因而限制了必须最佳使用的计量能力。在多个异构机器共享同一个计量车间的情况下,出现了在考虑计量能力的同时将风险最小化的问题。提出了整数线性规划(ILP)模型,该模型对应于多项选择背包问题。提出了简单的舍入启发法,将其在随机生成的实例上的结果与使用ILP上的标准求解器获得的最优解进行比较。此外,提出并讨论了工业数据的数值实验。

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